Relevant bibliographies by topics / Statistical energy analysis

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Statistical energy analysis'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Statistical energy analysis"

1

Le Bot, Alain. "Entropy in statistical energy analysis." Journal of the Acoustical Society of America 125, no. 3 (2009): 1473–78. http://dx.doi.org/10.1121/1.3075613.

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Mutani, Guglielmina, Silvia Santantonio, and Angelo Tartaglia. "Statistical Data Analysis for Energy Communities." TECNICA ITALIANA-Italian Journal of Engineering Science 64, no. 2-4 (2020): 385–97. http://dx.doi.org/10.18280/ti-ijes.642-438.

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Burroughs, Courtney B., Raymond W. Fischer, and Fred R. Kern. "An introduction to statistical energy analysis." Journal of the Acoustical Society of America 101, no. 4 (1997): 1779–89. http://dx.doi.org/10.1121/1.418074.

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Lu, L. "Statistical Energy Analysis for Electronic Equipment." Journal of Electronic Packaging 113, no. 3 (1991): 322–25. http://dx.doi.org/10.1115/1.2905413.

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Vibration response of electronic equipment analyzed by a simple mathematical model or a finite element model can only provide a limited system response calculation. Application of the Statistical Energy Analysis (SEA) was extended to the calculation of the vibrations of individual components. In order to demonstrate the applicability of SEA to instrumentation vibration analysis at high frequency ranges, an 8-component electronic box was chosen for test and analysis. There was good agreement between tested and analytical results in the frequency averaged sense.
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Lyon, Richard H. "Statistical energy analysis and structural fuzzy." Journal of the Acoustical Society of America 97, no. 5 (1995): 2878–81. http://dx.doi.org/10.1121/1.411854.

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Li, H., N. Totaro, L. Maxit, and A. Le Bot. "Ergodic billiard and statistical energy analysis." Wave Motion 87 (April 2019): 166–78. http://dx.doi.org/10.1016/j.wavemoti.2018.08.011.

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Le Bot, A., and V. Cotoni. "Validity diagrams of statistical energy analysis." Journal of Sound and Vibration 329, no. 2 (2010): 221–35. http://dx.doi.org/10.1016/j.jsv.2009.09.008.

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Ang, B. W. "A statistical analysis of energy coefficients." Energy Economics 13, no. 2 (1991): 93–110. http://dx.doi.org/10.1016/0140-9883(91)90041-w.

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Moeller, Mark J. "Visualization of statistical energy analysis results." Journal of the Acoustical Society of America 95, no. 5 (1994): 2900. http://dx.doi.org/10.1121/1.409318.

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Keane, A. J. "Statistical energy analysis of offshore structures." Engineering Structures 16, no. 2 (1994): 145–57. http://dx.doi.org/10.1016/0141-0296(94)90039-6.

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Dissertations / Theses on the topic "Statistical energy analysis"

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Whitehead, Andile. "Statistical-thermodynamical analysis, using Tsallis statistics, in high energy physics." Master's thesis, University of Cape Town, 2014. http://hdl.handle.net/11427/13391.

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Includes bibliographical references.<br>Obtained via the maximisation of a modified entropy, the Tsallis distribution has been used to fit the transverse momentum distributions of identified particles from several high energy experiments. We propose a form of the distribution described in Cleymans and Worku, 2012, and show it to be thermodynamically consistent. Transverse momenta distributions and fits from ALICE, ATLAS, and CMS using both Tsallis and Boltzmann distributions are presented.
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Keane, A. J. "Statistical energy analysis of engineering structures." Thesis, Brunel University, 1988. http://bura.brunel.ac.uk/handle/2438/5204.

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This thesis examines the fundamental equations of the branch of linear oscillatory dynamics known as Statistical Energy Analysis (SEA). The investigation described is limited to the study of two, point coupled multi-modal sub-systems which form the basis for most of the accepted theory in this field. Particular attention is paid to the development of exact classical solutions against which simplified approaches can be compared. These comparisons reveal deficiencies in the usual formulations of SEA in three areas, viz., for heavy damping, strong coupling between sub-systems and for systems with
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Chohan, Ghulam Yasin. "Statistical energy analysis of nonconservative dynamical systems." Thesis, University of Southampton, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.239507.

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Shorter, Philip. "Combining finite elements and statistical energy analysis /." Online version, 1998. http://bibpurl.oclc.org/web/23511.

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Skittides, Christina. "Statistical modelling of wind energy using Principal Component Analysis." Thesis, Heriot-Watt University, 2015. http://hdl.handle.net/10399/2930.

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The statistical method of Principal Component Analysis (PCA) is developed here from a time-series analysis method used in nonlinear dynamical systems to a forecasting tool and a Measure-Correlate-Predict (MCP) and then applied to wind speed data from a set of Met. Office stations from Scotland. PCA for time-series analysis is a method to separate coherent information from noise of measurements arising from some underlying dynamics and can then be used to describe the underlying dynamics. In the first step, this thesis shows that wind speed measurements from one or more weather stations can be
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Ezanno, Philippe. "Vibration localization and statistical energy analysis in coupled systems." Thesis, This resource online, 1990. http://scholar.lib.vt.edu/theses/available/etd-06112009-063056/.

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Connelly, Terence. "Structural vibration transmission in ships using statistical energy analysis." Thesis, Heriot-Watt University, 1999. http://hdl.handle.net/10399/1234.

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This thesis presents the results of an investigation into the application of statistical energy analysis (SEA) to predict structure-borne noise transmission in ship structures. The first three chapters introduce the problems of noise and vibration in ships; the previous research on the application of SEA to ships; the basic theory of SEA and the experimental measurement techniques and procedures used to gather data The main body of this thesis presents a wave transmission model for the hull frame joint which is commonly encountered on the hull, bulkheads and deck plates of ship structures. The
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Bashir, Hussam. "Calculation of Wave Propagation for Statistical Energy Analysis Models." Thesis, Uppsala universitet, Tillämpad mekanik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-267928.

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This thesis investigates the problems of applying Statistical Energy Analysis (SEA) tomodels that include solid volumes. Three wave types (Rayleigh waves, Pressure wavesand Shear waves) are important to SEA and the mathematics behind them is explainedhere. The transmission coefficients between the wave types are needed for energytransfer in SEA analysis and different approaches to solving the properties of wavepropagation on a solid volume are discussed. For one of the propagation problems, asolution, found in Momoi [6] is discussed, while the other problem remains unsolveddue to the analytica
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Lafont, Thibault. "Statistical vibroacoustics : study of SEA assumptions." Thesis, Ecully, Ecole centrale de Lyon, 2015. http://www.theses.fr/2015ECDL0003/document.

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La méthode SEA (Statistical Energy Analysis) est une approche statistique de la vibroacoustique permettant de décrire les systèmes complexes en termes d'échanges d'énergies vibratoires et acoustiques. En moyennes et hautes fréquences, cette méthode se présente comme une alternative aux méthodes déterministes (coût des calculs dû au grand nombre de modes, de degrés de liberté, unicité de la solution) Néanmoins, son utilisation requiert la connaissance et le respect d'hypothèses fortes qui limitent son domaine d'application. Dans ce mémoire, les fondements de la SEA ont été examinés afin de disc
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Mangisa, Siphumlile. "Statistical analysis of electricity demand profiles." Thesis, Nelson Mandela Metropolitan University, 2013. http://hdl.handle.net/10948/d1011548.

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An electricity demand profile is a graph showing the amount of electricity used by customers over a unit of time. It shows the variation in electricity demand versus time. In the demand profiles, the shape of the graph is of utmost importance. The variations in demand profiles are caused by many factors, such as economic and en- vironmental factors. These variations may also be due to changes in the electricity use behaviours of electricity users. This study seeks to model daily profiles of energy demand in South Africa with a model which is a composition of two de Moivre type models. The mode
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Books on the topic "Statistical energy analysis"

1

United States. National Aeronautics and Space Administration., ed. Asymptotic model analysis and statistical energy analysis. National Aeronautics and Space Administration, 1992.

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F, Peretti Linda, and United States. National Aeronautics and Space Administration., eds. Asymptotic modal analysis and statistical energy analysis. National Aeronautics and Space Administration, 1990.

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Fahy, F. J., and W. G. Price, eds. IUTAM Symposium on Statistical Energy Analysis. Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-015-9173-7.

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Keane, Andrew John. Statistical energy analysis of engineering structures. Brunel University, 1988.

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James, P. P. Weak coupling in statistical energy analysis. University of Southampton, Institute of Sound and Vibration Research, 1994.

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G, DeJong Richard, and Lyon Richard H, eds. Theory and application of statistical energy analysis. 2nd ed. Butterworth-Heinemann, 1995.

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Craik, Robert J. M. Sound transmission through buildings: Using statistical energy analysis. Gower, 1996.

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Orlóci, László. Quantum ecology: Energy structure and its analysis. 2nd ed. SCADA Publishing, 2014.

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James, P. P. Evolution of the energy impulse response in the case of two very weakly coupled systems: a mathematical model. University of Southampton, Institute of Sound and Vibration Research, 1995.

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J, Keane A., and Price W. G, eds. Statistical energy analysis: An overview, with applications in sturctural dynamics. Cambridge University Press, 1997.

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Book chapters on the topic "Statistical energy analysis"

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Crighton, D. G., A. P. Dowling, J. E. Ffowcs Williams, M. Heckl, and F. G. Leppington. "Statistical Energy Analysis." In Modern Methods in Analytical Acoustics. Springer London, 1992. http://dx.doi.org/10.1007/978-1-4471-0399-8_8.

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Wijker, Jaap. "Statistical Energy Analysis." In Random Vibrations in Spacecraft Structures Design. Springer Netherlands, 2009. http://dx.doi.org/10.1007/978-90-481-2728-3_4.

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Wijker, Jaap. "Statistical Energy Analysis." In Mechanical Vibrations in Spacecraft Design. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-662-08587-5_13.

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Ikeda, Yuichi. "Statistical Analysis." In Data Science of Renewable Energy Integration. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-8779-5_2.

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Manik, Dhanesh N. "Statistical Energy Analysis (SEA)." In Vibro-Acoustics. CRC Press, 2017. http://dx.doi.org/10.1201/9781315156729-10.

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Rindel, Jens Holger. "Statistical energy analysis, SEA." In Sound Insulation in Buildings. CRC Press, 2017. http://dx.doi.org/10.1201/9781351228206-8.

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Switzer, Paul. "Statistical Image Processing." In Quantitative Analysis of Mineral and Energy Resources. Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-009-4029-1_16.

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Mahoney, Daniel. "Data Analysis and Statistical Issues." In Modeling and Valuation of Energy Structures. Palgrave Macmillan UK, 2016. http://dx.doi.org/10.1057/9781137560155_2.

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Pradlwarter, H. J., and G. I. Schuëller. "Statistical Energy Analysis in View of Stochastic Modal Analysis." In IUTAM Symposium on Statistical Energy Analysis. Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-015-9173-7_19.

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Finnveden, S. "Statistical Energy Analysis of Fluid-Filled Pipes." In IUTAM Symposium on Statistical Energy Analysis. Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-015-9173-7_26.

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Conference papers on the topic "Statistical energy analysis"

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Nikolopoulos, Angelos R., Efstratios I. Batzelis, Paul Lewin, and Nikolaos Nikolaou. "Statistical Analysis of Solar Irradiance Variability." In 2024 IEEE Power & Energy Society General Meeting (PESGM). IEEE, 2024. http://dx.doi.org/10.1109/pesgm51994.2024.10689164.

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Yin, Gang, Federico Lucas, Rolf Balte, and John G. Cherng. "Experimental Variance Analysis of Statistical Energy Analysis." In SAE 2005 Noise and Vibration Conference and Exhibition. SAE International, 2005. http://dx.doi.org/10.4271/2005-01-2428.

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Radcliffe, Clark J., and Xian Li Huang. "Putting Statistics Into the Statistical Energy Analysis of Automotive Vehicles." In ASME 1993 Design Technical Conferences. American Society of Mechanical Engineers, 1993. http://dx.doi.org/10.1115/detc1993-0248.

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Abstract Sound and vibration transmission modeling methods are important to the design process for high quality automotive vehicles. Statistical Energy Analysis (SEA) is an emerging design tool for the automotive industry that was initially developed in the 1960’s to estimate root-mean-square sound and vibration levels in structures and interior spaces. Although developed to estimate statistical mean values, automotive design application of SEA needs the additional ability to predict statistical variances of the predicted mean values of sound and vibration. This analytical ability would allow
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CRAIK, RJM. "STATISTICAL ENERGY ANALYSIS THEORY INTO PRACTICE." In Spring Conference Acoustics 2000. Institute of Acoustics, 2024. http://dx.doi.org/10.25144/18605.

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CRAIK, RJM, and JA STEEL. "STATISTICAL ENERGY ANALYSIS AT LOW FREQUENCIES." In Acoustics '87 1987. Institute of Acoustics, 2024. http://dx.doi.org/10.25144/21982.

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Liao, Qingbin, and Shunming Li. "Statistical Response Prediction of Vehicle Based on Statistical Energy Analysis." In Asia Pacific Automotive Engineering Conference. SAE International, 2007. http://dx.doi.org/10.4271/2007-01-3498.

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Lyons, Louis. "Statistical techniques in high energy physics." In ADVANCED COMPUTING AND ANALYSIS TECHNIQUES IN PHYSICS RESEARCH: VII International Workshop; ACAT 2000. AIP, 2001. http://dx.doi.org/10.1063/1.1405258.

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Powell, Robert E. "Design Sensitivity Analysis of Statistical Energy Analysis Models." In SAE Noise and Vibration Conference and Exposition. SAE International, 1995. http://dx.doi.org/10.4271/951326.

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Moeller, Mark J., and Jian Pan. "Statistical Energy Analysis for Road Noise Simulation." In SAE Noise and Vibration Conference and Exposition. SAE International, 1997. http://dx.doi.org/10.4271/971972.

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MACE, BR, and L. JI. "THE STATISTICAL ENERGY ANALYSIS OF COUPLED OSCILLATORS." In Spring Conference Acoustics 2004. Institute of Acoustics, 2023. http://dx.doi.org/10.25144/17967.

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Reports on the topic "Statistical energy analysis"

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Maidanik, G., and K. J. Becker. Are the Energy Analysis (EA) and the Statistical Energy Analysis (SEA) Compatible? Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada419012.

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Pigni, Marco. R-MATRIX ANALYSIS AND STATISTICAL PROPERTIES OF DYSPROSIUM ISOTOPES IN THE NEUTRON ENERGY RANGES UP TO A FEW KEV. Office of Scientific and Technical Information (OSTI), 2023. http://dx.doi.org/10.2172/1987785.

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Leal, L. C. R-MATRIX RESONANCE ANALYSIS AND STATISTICAL PROPERTIES OF THE RESONANCE PARAMETERS OF 233U IN THE NEUTRON ENERGY RANGE FROM THERMAL TO 600 eV. Office of Scientific and Technical Information (OSTI), 2001. http://dx.doi.org/10.2172/777670.

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Linda Stetzenbach, Lauren Nemnich, and Davor Novosel. Statistical Analysis and Interpretation of Building Characterization, Indoor Environmental Quality Monitoring and Energy Usage Data from Office Buildings and Classrooms in the United States. Office of Scientific and Technical Information (OSTI), 2009. http://dx.doi.org/10.2172/1004553.

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Derrien, H. NEUTRON TOTAL CROSS SECTIONS OF 235U FROM TRANSMISSION MEASUREMENTS IN THE ENERGY RANGE 2 keV to 300 keV AND STATISTICAL MODEL ANALYSIS OF THE DATA. Office of Scientific and Technical Information (OSTI), 2000. http://dx.doi.org/10.2172/815777.

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Derrien, H., J. A. Harvey, N. M. Larson, L. C. Leal, and R. Q. Wright. Neutron Total Cross Sections of {sup 235}U From Transmission Measurements in the Energy Range 2 keV to 300 keV and Statistical Model Analysis of the Data. Office of Scientific and Technical Information (OSTI), 2000. http://dx.doi.org/10.2172/763240.

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Luo, Minjing, Yilin Li, Yingqiao Wang, et al. The Fragility of Statistically Significant Findings from Depression Randomized Controlled Trials. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2023. http://dx.doi.org/10.37766/inplasy2023.4.0086.

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Review question / Objective: The Fragility of Statistically Significant Findings from Depression Randomized Controlled Trials. Condition being studied: Depression is a mental disorder characterized by a range of symptoms, including loss of memory and sleep, decreased energy, feelings of guilt or low mood, disturbed appetite, poor concentration, and an increased risk of suicide. According to a systematic analysis of the Global Burden of Disease Study 2019, depression is recognized as the leading cause of disease burden for mental disorders, accounting for the largest proportion of disability-ad
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Kim, Joseph, and Patricia McCarthy. Evaluation of Sustainability Determinants to Develop a Sustainability Rating System for California Infrastructure Construction Projects. Mineta Transportation Institute, 2022. http://dx.doi.org/10.31979/mti.2022.2142.

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This study evaluates the important sustainability determinants that affect factors’ success in meeting their sustainability goals when conducting infrastructure construction projects in California. The study implemented the online survey method to evaluate the sustainability characteristics that infrastructure industry professionals currently are aware of under the current situation in California. A data set of 25 validated survey responses is used for statistical data analysis using analysis of variables, Kruskal-Wallis tests, and two sample t-tests. The analysis results showed that the media
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Tran, My-Thu, and Bo Yang. Using Thermal Remote Sensing to Quantify Impact of Traffic on Urban Heat Islands during COVID. Mineta Transportation Institute, 2023. http://dx.doi.org/10.31979/mti.2023.2207.

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A three-month lockdown in the U.S. at the beginning of the COVID-19 outbreak in 2020 greatly reduced the traffic volume in many cities, especially large metropolitan areas such as the San Francisco Bay Area. This research explores the impact of transportation on climate change by using remote sensing technology and statistical analysis during the COVID-19 lockdown. Using thermal satellite data, this research measures the intensity of the urban heat island, the main driver for climate change during the urbanization process. The research team acquired morning and afternoon MODIS data in the same
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Winikoff, Justin B., and Karen Maguire. The role of commercial energy payments in agricultural producer income. Economic Research Service, U.S. Department of Agriculture, 2024. http://dx.doi.org/10.32747/2024.8374827.ers.

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A significant portion of energy production in the United States takes place on farmland, which can have substantial economic implications for the farmers who host such developments. This report analyzes energy payments made to farmers for the production of oil, natural gas, and wind energy on their land. The authors used 10 years of data (2011-20) from the USDA's Agricultural Resource Management Survey (ARMS) in their analysis. Results show that 3.5 percent of farm operations received energy payments and that the average annual payment to the operators was more than $30,000 (in 2020 dollars),
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