Academic literature on the topic 'Numerical Rating Scale'

The landmark paper discussed in this chapter is ‘Clinical importance of changes in chronic pain intensity measured on an 11-point numerical pain rating scale’, published by Farrar et al. in 2001. The numerical rating scale is now the standard instrument used in chronic pain studies to measure pain intensity. Farrar et al. determined the changes in pain intensity that were clinically significant for studies of chronic pain while measuring the patient’s global impression of change. The paper used pooled data from ten recent studies of pregabalin in 2,724 subjects. The authors reported a consistent relationship between pain intensity and patient global impression of change, regardless of study, disease type, age, sex, study result, or treatment group. A reduction of approximately two points on the numerical rating scale, or of 30% in the global impression of change of pain intensity, represented a clinically important difference.

AbstractConcrete is a typical heterogeneous and multiscale material, and the macro-mechanical response is affected by the meso-scale geometric structure and mechanical parameters. Based on the continuum-discontinuum element method, this study conducts the numerical simulation and quantitively studies the change trend of macro-mechanical response with the different mesoscopic heterogeneity. First, a full-time numerical simulation is conducted, and the elastic modulus and cohesive strength at the meso-scale are assumed to obey the Weibull distribution. Then, the change trend of macro-mechanical parameters is studied. Finally, the change trend of crack evolution characteristic is studied. The results show that the macro-elastic modulus and macro-peak stress gradually increase with the increase of shape parameter k, and the growth rate of macro-mechanical parameters gradually decays. The difference in the shape parameter k causes the value of crack ratio to change, while the change trend of crack ratio-strain curve is similar. As the shape parameter k increases, the final value of crack ratio first decreases and then increases, and the final value of crack ratio when k = 15 is the smallest.

AbstractIn the paper, the influence of stress state and loading direction with respect to the principal axes of anisotropy on damage and fracture behavior of the anisotropic aluminum alloy EN AW-2017A is discussed. The focus is on numerical calculations on the micro-level considering void-containing representative volume elements revealing information on damage mechanisms. Using experimental data taken from uniaxial and biaxial tests, material parameters are identified. Based on numerical studies on the micro-scale with differently loaded void-containing cubes, it is shown that the stress state, the load ratio and the loading direction with respect to the principal axes of anisotropy have an influence on evolution of damage processes on the micro-scale and on the corresponding damage strains.

AbstractThe development and scaling out of flash-dryer innovations for more efficient, small-scale production of high-quality cassava flour (HQCF) and starch is described. The diagnoses of cassava-processing SMEs (small and medium enterprises) revealed their energy expenditures for drying were considerably higher than those of large-scale industrial companies, which was mostly due to suboptimal design of flash-drying systems. As a result, small-scale production of cassava starch and HQCF often incurs high production costs, incompatible with market prices of final products. Taking stock of this situation, RTB scientists have developed several innovations to optimize energy efficiency and costs, including a longer drying pipe, reengineered heat exchanger, larger blower for higher air velocity, and a higher product/air ratio. This was based on numerical modelling to determine the key design features of energy-efficient flash dryers, followed by construction and demonstration of a pilot-scale prototype. As a result, improved small-scale flash dryers are now being scaled out to the private sector in various countries, using the Scaling Readiness framework and achieving 10–15% gains in productivity and incomes. A method for diagnosis of process efficiency is also described, to identify technical bottlenecks and to document and measure the outcomes and impacts during the implementation of scaling-out projects.

AbstractRapid urbanization-induced poor ventilation makes it difficult for urban built-up environments to breathe fresh air and purify pollutants. Meanwhile, vehicle exhaust is emitted into urban streets and spread to nearby residential neighborhoods, severely threatening both the environmental quality of street space and the well-being of citizens residing adjacent to the road. The numerical simulation validated by wind tunnel measurements was adopted to examine the effects of the block scale (i.e. street length) on natural ventilation and exhaust pollutant dispersion within urban street canyons. The findings are as follows: (1) the airflow regime inside the street canyon is determined by the interaction of a canyon vortex at the middle and corner eddies at the ends, leading to notably elevated pollutant concentrations on its leeward and mid-section than on its windward and laterals; (2) the induced corner vortices at street ends can drive ambient pollutants toward the middle of the street canyon and subsequently be carried out by the canyon vortex, however there is a limit to this effect, which varies depending on the length of the street canyon with constant aspect ratio; (3) a proper block scale (street length) ranging from 200 m to 400 m is recommended, which could be used to strike a favorable balance between environmentally improving urban street air quality and morphologically creating a vibrant public space. Numerical simulation-based design strategies can be utilized to optimize existing urban design guidelines for creating a desirable scale in practical urban planning and construction.

Abstract We present well-resolved RANS simulations of two generic asymmetrically heated cooling channel configurations, a high aspect ratio cooling duct operated with liquid water at $$Re_b = 110 \times 10^3$$ and a cryogenic transcritical channel operated with methane at $$Re_b = 16 \times 10^3$$. The former setup serves to investigate the interaction of turbulence-induced secondary flow and heat transfer, and the latter to investigate the influence of strong non-linear thermodynamic property variations in the vicinity of the critical point on the flow field and heat transfer. To assess the accuracy of the RANS simulations for both setups, well-resolved implicit LES simulations using the adaptive local deconvolution method as subgrid-scale turbulence model serve as comparison databases. The investigation focuses on the prediction capabilities of RANS turbulence models for the flow as well as the temperature field and turbulent heat transfer with a special focus on the turbulent heat flux closure influence.

AbstractThe manufacturing of micro-scale components requires mastery of shaping processes ranging from micromechanics to electronic microfabrication. The hot embossing (HE) process is widely developed in various fields, since it allows to emboss complex structures at the micro/nanoscale such as optical sensors, diffractive lenses, microfluidic channels, and so on. The development of micro-structured parts via this process requires an in-depth analysis of the surface quality obtained and the mold filling rate. It is essential to analyze the influence of polymer properties to optimize the final mold filling to reduce cycle time and obtain defect-free replicated components. In this research, compression tests were carried out with poly(methyl methacrylate) (PMMA) and polycarbonate (PC), at different forming temperatures to determine their behavior law properties. Numerical simulation of the polymer forming processing was carried out by using Abaqus finite element software, taking into account the mechanical properties of both polymers and the characteristics of microchannels. The aim was to analyze the effect of the elastic–viscoplastic properties of the materials on the mold filling rate at different temperatures. Numerical simulation of the HE process with PMMA shows that the mold cavity is completely filled with elastic-viscoplastic behaviors, and the filling rate increases as a function of mold displacement. On the other hand, for PC, the embossed temperature has an influence on the filling ratio of the mold.

AbstractDifferent environmental issues such as carbonation and corrosion due to chloride threaten aging reinforced concrete (RC) bridges that are in service in areas highly prone to corrosion and earthquakes. Significant experimental and numerical efforts have been put into scrutinizing the effect of corrosion on nonlinear behavior of structural elements. With the rapid development of artificial intelligence, useful methods are now provided to allow for the assessment of such bridges without the drawbacks and limitations of the experimental and numerical methods. In this paper, four machine learning (ML) algorithms are employed; linear regression (LR), decision tree (DT), random forest (RF), and XGBoost for data fitting of the models, and Bayesian search is used for optimization of hyperparameters. Numerical models of RC piers with stochastic parameters defining geometry, loading, and materials are built, and the degradation due to corrosion is applied with a randomly determined level of corrosion. Then, the corroded models are nonlinearly analyzed with random ground motions scaled to design-based and maximum credible earthquake spectra, and maximum drift ratios are stored. Using the created database, different ML models are compared to find the most accurate one. R-squared, mean absolute error, mean squared error, and root mean squared error metrics are considered as the criteria for the selection of the most accurate model. LR model with R2 = 0.53, MAE = 0.0026, mean squared error (MSE) = 1.4 × 10−5, and root mean squared error (RMSE) = 0.0036 has the lowest accuracy while XGBoost with R2 = 0.8, MAE = 0.0015, MSE = 5 × 10−6, and RMSE = 0.0028 is the most accurate model. DT and RF models with R2 = 0.7 and R2 = 0.73, respectively, are in between.

AbstractDeployable coilable tape-spring booms have many advantages especially for use in space, such as light-weight, high folded-ratio and small storage volume. The boom’s folding and deploying process is accompanied with the large-scaled deformation of thin-walled materials, which may damage the boom on stress concentration points. For the sake of avoiding failures during coiling and deployment process, this paper aimed at acquiring the critical points on a boom which were vulnerable to be destroyed. Since the interactions of the boom’s infinitesimals were complicated, a numerical model was considered to be introduced. Meanwhile, the mechanical properties of the boom’s deployed state were also analyzed for a better design, and both the deploying and deployed behaviors were further analyzed through parametric study. The research of this paper will give more guidance on the design of tape-spring booms and the selection of the key parameters.

AbstractAll Components with H-shaped section are widely used in steel structures, in which the connection of beam section to column flange (i.e. weak-axis connection) is inevitable. In order to study the mechanical properties of weak-axis connected steel plate shear walls, a 1/3 scaled steel plate wall specimen was designed and subjected to a cyclic test to investigate the properties of stiffness, strength, ductility and energy dissipation. On the basis of this, the partially slotted steel plate shear wall was proposed. The FE model of the test specimen was developed and verified with the test results by FE software Abaqus. Subsequently, the FE model of the partially slotted steel plate wall was developed to study mechanical properties by comparing it with the test specimen. The analysis results show that the partially slotted infill plate can fully play the tension field and avoid the beam’s in-span bending, which effectively improves the structural ductility and energy consumption. Although the partially slotted infill plate will weaken the lateral resistance, the partially slotted SPSW still accounts for 75% of that one without slots in lateral bearing capacity. Additionally, the ductility of this partially slotted one is up to 5.79, and its equivalent viscous damping ratio reaches 30%.

Load rating of bridges is used to understand the working status and carrying capacity of bridge structures and components and is necessary to the safety of transportation. The current manual load rating procedure is, however, time-consuming. An intelligent and automatic load rating approach can be beneficial to supplement or eventually perhaps replace the current manual procedures. The innovation of this paper lies in developing an autonomous load rating framework by leveraging Digital Twin (DT) techniques. Full-scale laboratory testing of a bridge slab was conducted to verify the efficiency of the proposed framework. The ultimate moment capacity of the slab was obtained by carrying out four-point bending test. The testing procedure was monitored in real-time with multiple strain gauges. A real-scale finite element model of the slab was developed and calibrated with the testing results. The proposed DT framework of the bridge slabs was developed by integrating the numerical modeling and the strain monitoring. The proposed DT framework is intended for field application, and field results will be discussed.

Abstract Since decisions are invariably made within a given context, we model relative preferences as ratios of increments or decrements in an interval on the axis of desirability. Next, we sort the ratio magnitudes into a small number of categories, represented by numerical values on a geometric scale. We explain why the Analytic Hierarchy Process (AHP), typically based on a pairwise-comparison method, is concerned with category judgement of ratio magnitudes, whereas the Simple Multi-Attribute Rating Technique (SMART) essentially uses the orders of magnitude of these ratios. This provides a common basis for the analysis of the methods in question and for a cross-validation of their results. The present paper summarizes the basic assumptions and the relationship between the two methods.

<div class="section abstract"><div class="htmlview paragraph">Li-ion batteries are commonly used in Electric Vehicles (EVs) due to its high-power density and higher life cycle performance. Individual cells in such battery packs may sometimes lead to thermal runaway conditions under the effect of localized heat generation and faults. Battery liquid cooling methods are normally being employed to resolve this problem with limitations of limited temperature operating range and difficulty in reaching the intricate spaces between the cells. Introducing phase change material (PCM) can mitigate these limitations. The present study deals with a detailed numerical study of a single (Li-ion) cell in ANSYS Fluent using multi-scale multi dimension (MSMD) - Newman, Tiedenann, Gu and Kim (NTGK) model. The single cell model is investigated for the evaluation of its temperatures at varying air velocity surrounding the cell at higher C-rating (load) values. It was observed that the maximum cell surface temperatures were as 322.6, 319.8, 318.1, 316.9, 314.4 and 313.4 K corresponding to 0.5, 1.0, 1.5, 2.0, 2.5 and 3.0 m/s for 1.5C discharge rating. Further, the study also involved the investigation of composite PCM based on Paraffin and Vaseline (50:50; CPCM) for improving the cooling performance. It was found that the doping of 2% of Cu in CPCM resulted in ~8°C lower cell surface temperature.</div></div>

ABSTRACT Introduction: Artisanal and small-scale mining (ASM) is the extraction of ore with minimal to no mechanization by individuals or group of people who do not have advanced technical knowledge. Though ASM has gained considerable acceptance, one reason for its unsustainable is because of slope collapses that occur affecting the health and safety of miners and surrounding community. In rock mechanics, slope stability analysis and design has received significant attention in large scale mining to mitigate the risk of slope collapse but minimal implementation in artisanal and small-scale mining. This paper reports back the implementation of slope analysis and design through field observations to demonstrate the process of estimating rock mass rating (RMR) and finding suitable slope angles using Bieniawski (1976) RMR and Heins and Terbrugge stability charts respectively. Further analysis through laboratory strength tests and using numerical modelling software to assess the slope stability of the current and proposed slope design was conducted. Results: The slope design used in the ASM operation is unsuitable and the slope analysis using estimation charts required further analysis. Rock strength results were then used in OPTUM G2 to attempt to imitate reality. Suggested mining methods were proposed and mapped in OPTUM G2 where the limit equilibrium analysis showed that the gravity multiplier had increased by 10.04 for the upper limit and 2.79 for the lower limit and the strength reduction factor increased by 1.5. Significance: It is essential to continuously refine critical issues and help establish desirable conditions for ASM operations because it has a high potential to contribute towards sustainable development. Implementing cost-effective slope stability analysis systems for sustainable mining and promote achieving Sustainable Development Goal 1,3,8 and 9. Conclusion: The estimation process can be used with the guidance of a rock engineering practitioner during the design process of the mine after exposing the rock mass during the exploration stage. However, there may be other factors that can hinder the collection of data and modelling during the design phase as slope stability analysis systems were designed for large-scale mines.

In this work a steady state numerical analysis of the capillary effects in channels of a microscopic scale with rectangular cross section is presented. The diameter range under analysis falls on the microchannels classification. The velocities of the fluid flow satisfy the condition We<<Re, necessary and sufficient condition to guarantee that the capillary effects are present in the fluid flow in the channel. Water is used as the cooling fluid. A constant heat flux is applied at the heat sink bottom wall with a rating typical of the generated heat flow in current electronics high-tech devices. The results of thermal resistance are compared with the experimental results of Tuckerman, and the friction coefficient is compared with Peng and Peterson experiments, showing a good approximation when the capillary effects are considered in the numerical solution at lower Reynolds numbers.

Compressed Air Energy Storage is a promising large-scale storage system in part because of its high power rating during discharge. But it is not the cleanest way of storing energy due to the necessity of an external heat source (typically the combustion of natural gas) to heat the air at the turbine inlet. This problem can be overcome with Thermal Energy Storage by storing the thermal energy of air at the compressor exhaust in order to be used for heating air before turbine. In this study, a numerical transient heat transfer model of Thermal Energy Storage is developed and the performance of Thermal Energy Storage is investigated based on heat storage capacity, required time to store unit amount of energy and air temperature profiles at the outlet of Thermal Energy Storage during discharge for the system. High heat storage per volume is necessary for more compact systems. Required time to store unit amount of energy is desired to be short for a fixed volume Thermal Energy Storage in order to maintain continuous operation; on the other hand, air at the outlet (turbine inlet) should be at a high temperature for the longest time possible to supply hot air to turbine. In order to investigate the effects of operating parameters, different volumes of Thermal Energy Storage tank filled with different storage mediums of various sizes are explored. Latent Heat and Sensible Heat Thermal Energy Storage systems are compared using magnesium chloride hexahydrate, paraffin, myristic acid and naphthalene as phase change materials and rock as sensible storage medium. Results show that Latent Heat Thermal Energy Storage gives a better performance than Sensible Heat Thermal Energy Storage. Among phase change materials, magnesium chloride hexahydrate provides the highest heat storage per volume. Required time to store unit amount of energy are comparable among the phase change materials. Magnesium chloride hexahydrate seems promising considering the discharge temperature profile at the Thermal Energy Storage outlet. Capsule size should be kept as small as possible which can be challenging in terms of manufacturing.

Abstract A new type of actuation device has been conceptualized that meets the needs of both large displacement, force and bandwidth within a package more compact than currently available magnetostrictive and stack-type piezo actuators of similar rating. This concept relies on micro-scale electrohydrodynamic (EHD) pumping of a dielectric liquid with a small concentration of free charges. Configured as an actuator, the EHD pump(s) would be used to move fluid between two reservoirs — each having a compliant membrane that interfaces to the world to provide the means to achieve vibration cancellation or micro actuation. Ordinarily limited to generating flow in macroscale applications, the EHD pump is shown to exhibit an exciting scaling law as its size is reduced. As the pump volume to surface area decreases, the energy going toward increasing pressure in the pump has an increasingly larger effect. Since volume/surface area is proportional to 1/a2, where a is the characteristic width or diameter of the pump, the pressure head generated scales similarly. Analytical and numerical studies have shown the EHD-pumped actuator to be capable of delivering equal force and bandwidth to magnetostrictive and stack-type piezo actuators, but with consdierably greater displacement and roughly 1/10th of the size. Further, this type of actuator offers the possibility for deployment in active vibration control or micro actuation applications at significantly greater temperatures.

Buried pipelines subjected to non-continuous ground movement such as frost heave, thaw settlement, slope instability and seismic movement experience high compressive strains that can cause local buckling (or wrinkling), in which the pipe wall buckles like a thin cylindrical shell in axial compression. In a strain-based design and assessment framework, excessive local buckling deformation that may cause loss of serviceability, or even pressure containment in some cases, is managed by limiting the strain demand below the strain limit. The determination of compressive strain limit is typically performed by full-scale structural testing or nonlinear finite element analysis that takes into account material and geometric non-linearity associated with the inelastic buckling of cylindrical shells. Before performing testing and numerical analysis (or when such options do not exist), empirical equations are used to estimate the strain limit. In this report a number of representative equations were evaluated by comparing strain limit predictions to full-scale test results. Work prior to this study has identified the importance of key variables that have the greatest impact on the local buckling behaviour. Examples of these variables include the diameter-to-thickness (D/t) ratio, internal pressure and shape of the stress strain curve. The evaluation focused on how existing equations address these key variables, and the performance with respect to key variables and in different ranges.

Starting from Newton’s laws of motion and viscosity, this book is an introduction to fundamental aspects of fluid dynamics that are most relevant to groundwater scientists. Based on a perspective of driving versus resisting forces that govern the motion of a fluid, the author derives Darcy’s law for flow through porous media by drawing an analogy to Bernoulli’s law for fluid with negligible viscosity. By combining the effects of gravity and pressure, the author identifies hydraulic head as a convenient numerical quantity to represent the force driving groundwater flow. In contrast to the physical derivation of hydraulic head, hydraulic conductivity emerges as a parameter related to the resisting frictional forces between the mobile fluid and the stationary porous medium. These frictional seepage forces also affect the effective stress state of the porous medium, thus establishing a link to soil stability and quicksand formation. Combining Darcy’s law with the law of mass conservation leads the reader to the fundamental equations of saturated groundwater flow. Finally, the effects of capillary forces are included to establish the governing equations for unsaturated and multi-phase flow. Throughout the book, the author focuses on thoroughly illustrating and deriving the equations while applying order of magnitude analyses. This approach makes it possible to extract the most information, for example in terms of the scale of response time, without requiring explicit solutions. A number of boxes and solved exercises contain further details and links to practical applications such as the water table ratio that reflects ‘fullness’ of an aquifer and the performance of slug tests for in situ measurement of hydraulic conductivity. This book makes an important contribution to groundwater science by providing a progressive introductory explanation of the physical mechanics of groundwater flow and the accompanying socioeconomic and ecological problems that may arise.

Background and Objectives: The incidence of post-procedural pain following percutaneous thermal liver ablation under procedural sedation and analgesia (PSA) is yet largely unknown. Only a few small studies investigated tumor and ablation factors on pain, whereas psychological or PSA factors as possible predictors for pain were not investigated. The primary aim of the current study is to measure the prevalence and severity of post-procedural pain based on maximal NRS. Secondary aim of this study is to identify predictors for post procedural pain post liver ablation under PSA. Methods: This single center retrospective cohort study was conducted in a tertiary teaching hospital in the Netherlands from November 2018 until May 2023. It involved adult patients (18 years or older) treated with thermal liver ablation under PSA. Prevalence of pain was based on percentage of patients with post-procedural pain (defined as numeric rating scale (NRS) score ≥4). Results: In total, 170 records of 117 patients were included in the analysis of this study. The prevalence of post- procedural pain after thermal liver ablation was 42.7%. Predictors of post-ablation pain were psychological factors e.g. depression, anxiety disorder or the use of psychopharmacological drugs (β 2.58, 95%CI: 1.44-4.07, p-value<0,001). A background of chronic pain (β 1.23, 95%CI: 0.11-2.36, p-value 0.03), female gender (β 1.09, 95%CI: 0.17-2.01, p-value 0.02) and age (β -0.04 per calendar year, 95%CI: -0.091- -0.006, p-value 0.05) were shown to predict acute ablation pain. Tumor location, distinction between primary and secondary tumors and number of tumors did not predict post-ablation pain. Conclusion: The incidence of post-procedural pain after thermal liver ablation is 42.7%. Predictive factors of post procedural pain after thermal liver ablation under PSA are psychological factors like depression and anxiety as well as the use of psychopharmacological drugs. Tumor characteristics did not predict post-procedural pain after ablation.

Background and Objectives: The incidence of post-procedural pain following percutaneous thermal liver ablation under procedural sedation and analgesia (PSA) is yet largely unknown. Only a few small studies investigated tumor and ablation factors on pain, whereas psychological or PSA factors as possible predictors for pain were not investigated. The primary aim of the current study is to measure the prevalence and severity of post-procedural pain based on maximal NRS. Secondary aim of this study is to identify predictors for post procedural pain post liver ablation under PSA. Methods: This single center retrospective cohort study was conducted in a tertiary teaching hospital in the Netherlands from November 2018 until May 2023. It involved adult patients (18 years or older) treated with thermal liver ablation under PSA. Prevalence of pain was based on percentage of patients with post-procedural pain (defined as numeric rating scale (NRS) score ≥4). Results: In total, 170 records of 117 patients were included in the analysis of this study. The prevalence of post- procedural pain after thermal liver ablation was 42.7%. Predictors of post-ablation pain were psychological factors e.g. depression, anxiety disorder or the use of psychopharmacological drugs (β 2.58, 95%CI: 1.44-4.07, p-value<0,001). A background of chronic pain (β 1.23, 95%CI: 0.11-2.36, p-value 0.03), female gender (β 1.09, 95%CI: 0.17-2.01, p-value 0.02) and age (β -0.04 per calendar year, 95%CI: -0.091- -0.006, p-value 0.05) were shown to predict acute ablation pain. Tumor location, distinction between primary and secondary tumors and number of tumors did not predict post-ablation pain. Conclusion: The incidence of post-procedural pain after thermal liver ablation is 42.7%. Predictive factors of post procedural pain after thermal liver ablation under PSA are psychological factors like depression and anxiety as well as the use of psychopharmacological drugs. Tumor characteristics did not predict post-procedural pain after ablation.

This report is one of a series of reports documenting the methods and findings of a multi-year, multi-disciplinary project coordinated by the Pacific Earthquake Engineering Research Center (PEER) and funded by the California Earthquake Authority (CEA). The overall project is titled “Quantifying the Performance of Retrofit of Cripple Walls and Sill Anchorage in Single-Family Wood-Frame Buildings,” henceforth referred to as the “PEER–CEA Project.” The overall objective of the PEER–CEA Project is to provide scientifically based information (e.g., testing, analysis, and resulting loss models) that measure and assess the effectiveness of seismic retrofit to reduce the risk of damage and associated losses (repair costs) of wood-frame houses with cripple wall and sill anchorage deficiencies as well as retrofitted conditions that address those deficiencies. Tasks that support and inform the loss-modeling effort are: (1) collecting and summarizing existing information and results of previous research on the performance of wood-frame houses; (2) identifying construction features to characterize alternative variants of wood-frame houses; (3) characterizing earthquake hazard and ground motions at representative sites in California; (4) developing cyclic loading protocols and conducting laboratory tests of cripple wall panels, wood-frame wall subassemblies, and sill anchorages to measure and document their response (strength and stiffness) under cyclic loading; and (5) the computer modeling, simulations, and the development of loss models as informed by a workshop with claims adjustors. This report is a product of Working Group 3 (WG3), Task 3.1: Selecting and Scaling Ground-motion records. The objective of Task 3.1 is to provide suites of ground motions to be used by other working groups (WGs), especially Working Group 5: Analytical Modeling (WG5) for Simulation Studies. The ground motions used in the numerical simulations are intended to represent seismic hazard at the building site. The seismic hazard is dependent on the location of the site relative to seismic sources, the characteristics of the seismic sources in the region and the local soil conditions at the site. To achieve a proper representation of hazard across the State of California, ten sites were selected, and a site-specific probabilistic seismic hazard analysis (PSHA) was performed at each of these sites for both a soft soil (Vs30 = 270 m/sec) and a stiff soil (Vs30=760 m/sec). The PSHA used the UCERF3 seismic source model, which represents the latest seismic source model adopted by the USGS [2013] and NGA-West2 ground-motion models. The PSHA was carried out for structural periods ranging from 0.01 to 10 sec. At each site and soil class, the results from the PSHA—hazard curves, hazard deaggregation, and uniform-hazard spectra (UHS)—were extracted for a series of ten return periods, prescribed by WG5 and WG6, ranging from 15.5–2500 years. For each case (site, soil class, and return period), the UHS was used as the target spectrum for selection and modification of a suite of ground motions. Additionally, another set of target spectra based on “Conditional Spectra” (CS), which are more realistic than UHS, was developed [Baker and Lee 2018]. The Conditional Spectra are defined by the median (Conditional Mean Spectrum) and a period-dependent variance. A suite of at least 40 record pairs (horizontal) were selected and modified for each return period and target-spectrum type. Thus, for each ground-motion suite, 40 or more record pairs were selected using the deaggregation of the hazard, resulting in more than 200 record pairs per target-spectrum type at each site. The suites contained more than 40 records in case some were rejected by the modelers due to secondary characteristics; however, none were rejected, and the complete set was used. For the case of UHS as the target spectrum, the selected motions were modified (scaled) such that the average of the median spectrum (RotD50) [Boore 2010] of the ground-motion pairs follow the target spectrum closely within the period range of interest to the analysts. In communications with WG5 researchers, for ground-motion (time histories, or time series) selection and modification, a period range between 0.01–2.0 sec was selected for this specific application for the project. The duration metrics and pulse characteristics of the records were also used in the final selection of ground motions. The damping ratio for the PSHA and ground-motion target spectra was set to 5%, which is standard practice in engineering applications. For the cases where the CS was used as the target spectrum, the ground-motion suites were selected and scaled using a modified version of the conditional spectrum ground-motion selection tool (CS-GMS tool) developed by Baker and Lee [2018]. This tool selects and scales a suite of ground motions to meet both the median and the user-defined variability. This variability is defined by the relationship developed by Baker and Jayaram [2008]. The computation of CS requires a structural period for the conditional model. In collaboration with WG5 researchers, a conditioning period of 0.25 sec was selected as a representative of the fundamental mode of vibration of the buildings of interest in this study. Working Group 5 carried out a sensitivity analysis of using other conditioning periods, and the results and discussion of selection of conditioning period are reported in Section 4 of the WG5 PEER report entitled Technical Background Report for Structural Analysis and Performance Assessment. The WG3.1 report presents a summary of the selected sites, the seismic-source characterization model, and the ground-motion characterization model used in the PSHA, followed by selection and modification of suites of ground motions. The Record Sequence Number (RSN) and the associated scale factors are tabulated in the Appendices of this report, and the actual time-series files can be downloaded from the PEER Ground-motion database Portal (https://ngawest2.berkeley.edu/)(link is external).

Considering the importance of the transportation network and bridge structures, the associated seismic design philosophy is shifting from the basic collapse prevention objective to maintaining functionality on the community scale in the aftermath of moderate to strong earthquakes (i.e., resiliency). In addition to performance, the associated construction philosophy is also being modernized, with the utilization of accelerated bridge construction (ABC) techniques to reduce impacts of construction work on traffic, society, economy, and on-site safety during construction. Recent years have seen several developments towards the design of low-damage bridges and ABC. According to the results of conducted tests, these systems have significant potential to achieve the intended community resiliency objectives. Taking advantage of such potential in the standard design and analysis processes requires proper modeling that adequately characterizes the behavior and response of these bridge systems. To evaluate the current practices and abilities of the structural engineering community to model this type of resiliency-oriented bridges, the Pacific Earthquake Engineering Research Center (PEER) organized a blind prediction contest of a two-column bridge bent consisting of columns with enhanced response characteristics achieved by a well-balanced contribution of self-centering, rocking, and energy dissipation. The parameters of this blind prediction competition are described in this report, and the predictions submitted by different teams are analyzed. In general, forces are predicted better than displacements. The post-tension bar forces and residual displacements are predicted with the best and least accuracy, respectively. Some of the predicted quantities are observed to have coefficient of variation (COV) values larger than 50%; however, in general, the scatter in the predictions amongst different teams is not significantly large. Applied ground motions (GM) in shaking table tests consisted of a series of naturally recorded earthquake acceleration signals, where GM1 is found to be the largest contributor to the displacement error for most of the teams, and GM7 is the largest contributor to the force (hence, the acceleration) error. The large contribution of GM1 to the displacement error is due to the elastic response in GM1 and the errors stemming from the incorrect estimation of the period and damping ratio. The contribution of GM7 to the force error is due to the errors in the estimation of the base-shear capacity. Several teams were able to predict forces and accelerations with only moderate bias. Displacements, however, were systematically underestimated by almost every team. This suggests that there is a general problem either in the assumptions made or the models used to simulate the response of this type of bridge bent with enhanced response characteristics. Predictions of the best-performing teams were consistently and substantially better than average in all response quantities. The engineering community would benefit from learning details of the approach of the best teams and the factors that caused the models of other teams to fail to produce similarly good results. Blind prediction contests provide: (1) very useful information regarding areas where current numerical models might be improved; and (2) quantitative data regarding the uncertainty of analytical models for use in performance-based earthquake engineering evaluations. Such blind prediction contests should be encouraged for other experimental research activities and are planned to be conducted annually by PEER.

Executive Summary This report describes a series of experiments carried out by PRICE Lab, a research programme at the Economic and Social Research Institute (ESRI) jointly funded by the Central Bank of Ireland, the Commission for Energy Regulation, the Competition and Consumer Protection Commission and the Commission for Communications Regulation. The experiments were conducted with samples of Irish consumers aged 18-70 years and were designed to answer the following general research question: At what point do products become too complex for consumers to choose accurately between the good ones and the bad ones? BACKGROUND AND METHODS PRICE Lab represents a departure from traditional methods employed for economic research in Ireland. It belongs to the rapidly expanding area of ‘behavioural economics’, which is the application of psychological insights to economic analysis. In recent years, behavioural economics has developed novel methods and generated many new findings, especially in relation to the choices made by consumers. These scientific advances have implications both for economics and for policy. They suggest that consumers often do not make decisions in the way that economists have traditionally assumed. The findings show that consumers have limited capacity for attending to and processing information and that they are prone to systematic biases, all of which may lead to disadvantageous choices. In short, consumers may make costly mistakes. Research has indeed documented that in several key consumer markets, including financial services, utilities and telecommunications, many consumers struggle to choose the best products for themselves. It is often argued that these markets involve ‘complex’ products. The obvious question that arises is whether consumer policy can be used to help them to make better choices when faced with complex products. Policies are more likely to be successful where they are informed by an accurate understanding of how real consumers make decisions between products. To provide evidence for consumer policy, PRICE Lab has developed a method for measuring the accuracy with which consumers make choices, using techniques adapted from the scientific study of human perception. The method allows researchers to measure how reliably consumers can distinguish a good deal from a bad one. A good deal is defined here as one where the product is more valuable than the price paid. In other words, it offers good value for money or, in the jargon of economics, offers the consumer a ‘surplus’. Conversely, a bad deal offers poor value for money, providing no (or a negative) surplus. PRICE Lab’s main experimental method, which we call the ‘Surplus Identification’ (S-ID) task, allows researchers to measure how accurately consumers can spot a surplus and whether they are prone to systematic biases. Most importantly, the S-ID task can be used to study how the accuracy of consumers’ decisions changes as the type of product changes. For the experiments we report here, samples of consumers arrived at the ESRI one at a time and spent approximately one hour doing the S-ID task with different kinds of products, which were displayed on a computer screen. They had to learn to judge the value of one or more products against prices and were then tested for accuracy. As well as people’s intrinsic motivation to do well when their performance on a task like this is tested, we provided an incentive: one in every ten consumers who attended PRICE Lab won a prize, based on their performance. Across a series of these experiments, we were able to test how the accuracy of consumers’ decisions was affected by the number and nature of the product’s characteristics, or ‘attributes’, which they had to take into account in order to distinguish good deals from bad ones. In other words, we were able to study what exactly makes for a ‘complex’ product, in the sense that consumers find it difficult to choose good deals. FINDINGS Overall, across all ten experiments described in this report, we found that consumers’ judgements of the value of products against prices were surprisingly inaccurate. Even when the product was simple, meaning that it consisted of just one clearly perceptible attribute (e.g. the product was worth more when it was larger), consumers required a surplus of around 16-26 per cent of the total price range in order to be able to judge accurately that a deal was a good one rather than a bad one. Put another way, when most people have to map a characteristic of a product onto a range of prices, they are able to distinguish at best between five and seven levels of value (e.g. five levels might be thought of as equivalent to ‘very bad’, ‘bad’, ‘average’, ‘good’, ‘very good’). Furthermore, we found that judgements of products against prices were not only imprecise, but systematically biased. Consumers generally overestimated what products at the top end of the range were worth and underestimated what products at the bottom end of the range were worth, typically by as much as 10-15 per cent and sometimes more. We then systematically increased the complexity of the products, first by adding more attributes, so that the consumers had to take into account, two, three, then four different characteristics of the product simultaneously. One product might be good on attribute A, not so good on attribute B and available at just above the xii | PRICE Lab: An Investigation of Consumers’ Capabilities with Complex Products average price; another might be very good on A, middling on B, but relatively expensive. Each time the consumer’s task was to judge whether the deal was good or bad. We would then add complexity by introducing attribute C, then attribute D, and so on. Thus, consumers had to negotiate multiple trade-offs. Performance deteriorated quite rapidly once multiple attributes were in play. Even the best performers could not integrate all of the product information efficiently – they became substantially more likely to make mistakes. Once people had to consider four product characteristics simultaneously, all of which contributed equally to the monetary value of the product, a surplus of more than half the price range was required for them to identify a good deal reliably. This was a fundamental finding of the present experiments: once consumers had to take into account more than two or three different factors simultaneously their ability to distinguish good and bad deals became strikingly imprecise. This finding therefore offered a clear answer to our primary research question: a product might be considered ‘complex’ once consumers must take into account more than two or three factors simultaneously in order to judge whether a deal is good or bad. Most of the experiments conducted after we obtained these strong initial findings were designed to test whether consumers could improve on this level of performance, perhaps for certain types of products or with sufficient practice, or whether the performance limits uncovered were likely to apply across many different types of product. An examination of individual differences revealed that some people were significantly better than others at judging good deals from bad ones. However the differences were not large in comparison to the overall effects recorded; everyone tested struggled once there were more than two or three product attributes to contend with. People with high levels of numeracy and educational attainment performed slightly better than those without, but the improvement was small. We also found that both the high level of imprecision and systematic bias were not reduced substantially by giving people substantial practice and opportunities to learn – any improvements were slow and incremental. A series of experiments was also designed to test whether consumers’ capability was different depending on the type of product attribute. In our initial experiments the characteristics of the products were all visual (e.g., size, fineness of texture, etc.). We then performed similar experiments where the relevant product information was supplied as numbers (e.g., percentages, amounts) or in categories (e.g., Type A, Rating D, Brand X), to see whether performance might improve. This question is important, as most financial and contractual information is supplied to consumers in a numeric or categorical form. The results showed clearly that the type of product information did not matter for the level of imprecision and bias in consumers’ decisions – the results were essentially the same whether the product attributes were visual, numeric or categorical. What continued to drive performance was how many characteristics the consumer had to judge simultaneously. Thus, our findings were not the result of people failing to perceive or take in information accurately. Rather, the limiting factor in consumers’ capability was how many different factors they had to weigh against each other at the same time. In most of our experiments the characteristics of the product and its monetary value were related by a one-to-one mapping; each extra unit of an attribute added the same amount of monetary value. In other words, the relationships were all linear. Because other findings in behavioural economics suggest that consumers might struggle more with non-linear relationships, we designed experiments to test them. For example, the monetary value of a product might increase more when the amount of one attribute moves from very low to low, than when it moves from high to very high. We found that this made no difference to either the imprecision or bias in consumers’ decisions provided that the relationship was monotonic (i.e. the direction of the relationship was consistent, so that more or less of the attribute always meant more or less monetary value respectively). When the relationship involved a turning point (i.e. more of the attribute meant higher monetary value but only up to a certain point, after which more of the attribute meant less value) consumers’ judgements were more imprecise still. Finally, we tested whether familiarity with the type of product improved performance. In most of the experiments we intentionally used products that were new to the experimental participants. This was done to ensure experimental control and so that we could monitor learning. In the final experiment reported here, we used two familiar products (Dublin houses and residential broadband packages) and tested whether consumers could distinguish good deals from bad deals any better among these familiar products than they could among products that they had never seen before, but which had the same number and type of attributes and price range. We found that consumers’ performance was the same for these familiar products as for unfamiliar ones. Again, what primarily determined the amount of imprecision and bias in consumers’ judgments was the number of attributes that they had to balance against each other, regardless of whether these were familiar or novel. POLICY IMPLICATIONS There is a menu of consumer polices designed to assist consumers in negotiating complex products. A review, including international examples, is given in the main body of the report. The primary aim is often to simplify the consumer’s task. Potential policies, versions of which already exist in various forms and which cover a spectrum of interventionist strength, might include: the provision and endorsement of independent, transparent price comparison websites and other choice engines (e.g. mobile applications, decision software); the provision of high quality independent consumer advice; ‘mandated simplification’, whereby regulations stipulate that providers must present product information in a simplified and standardised format specifically determined by regulation; and more strident interventions such as devising and enforcing prescriptive rules and regulations in relation to permissible product descriptions, product features or price structures. The present findings have implications for such policies. However, while the experimental findings have implications for policy, it needs to be borne in mind that the evidence supplied here is only one factor in determining whether any given intervention in markets is likely to be beneficial. The findings imply that consumers are likely to struggle to choose well in markets with products consisting of multiple important attributes that must all be factored in when making a choice. Interventions that reduce this kind of complexity for consumers may therefore be beneficial, but nothing in the present research addresses the potential costs of such interventions, or how providers are likely to respond to them. The findings are also general in nature and are intended to give insights into consumer choices across markets. There are likely to be additional factors specific to certain markets that need to be considered in any analysis of the costs and benefits of a potential policy change. Most importantly, the policy implications discussed here are not specific to Ireland or to any particular product market. Furthermore, they should not be read as criticisms of existing regulatory regimes, which already go to some lengths in assisting consumers to deal with complex products. Ireland currently has extensive regulations designed to protect consumers, both in general and in specific markets, descriptions of which can be found in Section 9.1 of the main report. Nevertheless, the experiments described here do offer relevant guidance for future policy designs. For instance, they imply that while policies that make it easier for consumers to switch providers may be necessary to encourage active consumers, they may not be sufficient, especially in markets where products are complex. In order for consumers to benefit, policies that help them to identify better deals reliably may also be required, given the scale of inaccuracy in consumers’ decisions that we record in this report when products have multiple important attributes. Where policies are designed to assist consumer decisions, the present findings imply quite severe limits in relation to the volume of information consumers can simultaneously take into account. Good impartial Executive Summary | xv consumer advice may limit the volume of information and focus on ensuring that the most important product attributes are recognised by consumers. The findings also have implications for the role of competition. While consumers may obtain substantial potential benefits from competition, their capabilities when faced with more complex products are likely to reduce such benefits. Pressure from competition requires sufficient numbers of consumers to spot and exploit better value offerings. Given our results, providers with larger market shares may face incentives to increase the complexity of products in an effort to dampen competitive pressure and generate more market power. Where marketing or pricing practices result in prices or attributes with multiple components, our findings imply that consumer choices are likely to become less accurate. Policymakers must of course be careful in determining whether such practices amount to legitimate innovations with potential consumer benefit. Yet there is a genuine danger that spurious complexity can be generated that confuses consumers and protects market power. The results described here provide backing for the promotion and/or provision by policymakers of high-quality independent choice engines, including but not limited to price comparison sites, especially in circumstances where the number of relevant product attributes is high. A longer discussion of the potential benefits and caveats associated with such policies is contained in the main body of the report. Mandated simplification policies are gaining in popularity internationally. Examples include limiting the number of tariffs a single energy company can offer or standardising health insurance products, both of which are designed to simplify the comparisons between prices and/or product attributes. The present research has some implications for what might make a good mandate. Consumer decisions are likely to be improved where a mandate brings to the consumer’s attention the most important product attributes at the point of decision. The present results offer guidance with respect to how many key attributes consumers are able simultaneously to trade off, with implications for the design of standardised disclosures. While bearing in mind the potential for imposing costs, the results also suggest benefits to compulsory ‘meta-attributes’ (such as APRs, energy ratings, total costs, etc.), which may help consumers to integrate otherwise separate sources of information. FUTURE RESEARCH The experiments described here were designed to produce findings that generalise across multiple product markets. However, in addition to the results outlined in this report, the work has resulted in new experimental methods that can be applied to more specific consumer policy issues. This is possible because the methods generate experimental measures of the accuracy of consumers’ decision-making. As such, they can be adapted to assess the quality of consumers’ decisions in relation to specific products, pricing and marketing practices. Work is underway in PRICE Lab that applies these methods to issues in specific markets, including those for personal loans, energy and mobile phones.

As a promising composite structure, gangue concrete filled steel tubular (GCFST) column exhibites favarable characteristics including high strength and economic efficiency. This paper conducted numerical investiagations on structural behavior of a ring-beam connection to GCFST column with concrete beam under cyclic loading. Furthermore, finite element models of column-beam connections were developed using ABAQUS and validated against full-scale experimental tests to identify accuracy of selected modeling approaches. Using these validated models, stress distribution of each component was examined to study the force-transferring mechanism among the components and failure modes of the ring-beam connection. Research study indicated that the ring-beam connection showed a reasonable force-transferring mechanism under cyclic loading and the remarkable earthquake-resistant performance with high capacity and acceptable ductility. Finally, parametric studies were performed to assess the influences of beam-to-column stiffness ratio,steel ratio, axial load level, and concrete compressive strength on connection cyclic behaviors. Parametric studies provided some suggestions and references for the application of the ring-beam connection in various engineering projects.

The cyclic behavior of tree-like hollow structural section (HSS) columns with infilled concrete was experimentally and numerically investigated. A full-scale column, with the height of 3.2 m and the treetop plan dimension of 4 m×3 m, was designed and manufactured according to a practical engineering prototype. The column with a capacity protected reinforced concrete foundation was tested under combined constant axial compression and cyclic lateral loading through a specifically designed setup. The cracking and spalling of the reinforced concrete foundation were observed initially, followed by yielding of the bottom end of the primary branches when the story drift ratio reached 1.00%. The specimen failed by fracture of the full penetration groove welded splices in the petal-shaped trunk embedded in the foundation when the story drift ratio reached 3.00%. A detailed finite element analysis model for the tree-like column was then established and verified. Parametric studies were conducted to investigate the influence of the axial load level, filling range of concrete, steel yield strength, and the height to width ratio of the petal-shaped trunk. Finally, some design considerations were proposed.