Relevant bibliographies by topics / Methods of three-dimensional optimization

Contents

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

Academic literature on the topic 'Methods of three-dimensional optimization'

Author: Grafiati
Published: 30 May 2022
Last updated: 31 July 2025

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Journal articles on the topic "Methods of three-dimensional optimization"

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Shang, Kun, and Kai Zhang. "Three-Dimensional Sonar Imaging Software on the DSP." Advanced Materials Research 219-220 (March 2011): 49–52. http://dx.doi.org/10.4028/www.scientific.net/amr.219-220.49.

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This paper has explored the design of three-dimensional imaging sonar software and its application to the hardware platform. In the process of designing, the software has been optimized in view of characteristics of the hardware structures and calculation of the TMS320C6416, and the specific optimization methods and effects have also been presented. It turns out that the effect of software optimization is obvious and the working system stable and reliable.
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Brune, Alexander, and Michal Kočvara. "On Barrier and Modified Barrier Multigrid Methods for Three-Dimensional Topology Optimization." SIAM Journal on Scientific Computing 42, no. 1 (2020): A28—A53. http://dx.doi.org/10.1137/19m1254490.

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Rebai, Maher, Matthieu le Berre, Faicel Hnaien, and Hichem Snoussi. "Exact Biobjective Optimization Methods for Camera Coverage Problem in Three-Dimensional Areas." IEEE Sensors Journal 16, no. 9 (2016): 3323–31. http://dx.doi.org/10.1109/jsen.2016.2519451.

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Simonetti, Hélio Luiz, Valério Silva Almeida, Francisco de Assis das Neves, Vírgil Del Duca Almeida, and Luttgardes de Oliveira Neto. "Reliability-Based Topology Optimization: An Extension of the SESO and SERA Methods for Three-Dimensional Structures." Applied Sciences 12, no. 9 (2022): 4220. http://dx.doi.org/10.3390/app12094220.

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This study takes an approach to reliability-based topology optimization (RBTO) for 3D structures by applying an expansion of smoothing evolutionary structural optimization (SESO) and sequential element rejection and admission (SERA) for three-dimensional optimization. In the search for the stable optimal solution, and a more reliable structure, we present a performance index with the ability to monitor the evolutionary optimization procedure and adopt the filtering scheme usually applied in solid isotropic material with penalization (SIMP). The limit state functions are the maximum displacemen
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Vozniak, Oleh, and Valery Korobov. "Time-optimal controlonasubspaceforthetwoand three-dimensional system." V. N. Karazin Kharkiv National University. Ser. Mathematics, Applied Mathematics and Mechanics, no. 100 (December 23, 2024): 48–60. https://doi.org/10.26565/2221-5646-2024-100-03.

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This article is devoted to the problem of the optimal synthesis on a subspace for the 2 and 3-dimensional case for the linear control system $\dot{x_1} = u, \dot{x}_i=x_{i-1}, i=\overline{2,n}$ with $|u|\le1$. This problem is related to the problem of optimal synthesis into the point, which solution was presented by V. I. Korobov and G. M. Sklyar and is based on the moment min-problem, but its difference with respect to the original problem is that the number of unknown functions is greater than the number of variables, which requires using the methods for the parametric optimization. As in th
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von den Hoff, Bieke, Roberto Merino-Martínez, Dick G. Simons, and Mirjam Snellen. "Using global optimization methods for three-dimensional localization and quantification of incoherent acoustic sources." JASA Express Letters 2, no. 5 (2022): 054802. http://dx.doi.org/10.1121/10.0010456.

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Complex acoustic systems typically present three-dimensional distributions of noise sources. Conventional acoustic imaging methods with planar microphone arrays are unsuitable for three-dimensional acoustic imaging, given the computational demands and the incapability to explicitly account for the presence of multiple sources. This paper proposes the use of global optimization methods to solve these shortcomings. An experiment with three incoherent speakers proved that this method can accurately determine the three-dimensional location and the respective sound level of each individual source.
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Kureychik, Vladimir, Vladislav Danilchenko, and Evgeniya Danilchenko. "Routing of Autonomous Devices in Three-Dimensional Space." Informatics and Automation 24, no. 2 (2025): 492–525. https://doi.org/10.15622/ia.24.2.5.

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The article addresses the problem of routing autonomous devices in three-dimensional space, which is a relevant task for intelligent control. The three-dimensional space is characterized by a high degree of freedom, complex topology, and dynamic environmental changes, which significantly complicate the task of effective trajectory planning. The development of routing methods that ensure safety, energy efficiency, and computational efficiency is crucial for improving the performance of autonomous systems. The paper presents a comprehensive routing system based on a hybrid approach that combines
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Zangeneh, M., A. Goto, and H. Harada. "On the role of three-dimensional inverse design methods in turbomachinery shape optimization." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 213, no. 1 (1999): 27–42. http://dx.doi.org/10.1243/0954406991522167.

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The application of a three-dimensional (3D) inverse design method in which the blade geometry is computed for a specified distribution of circulation to the design of turbomachinery blades is explored by using two examples. In the first instance the method is applied to the design of radial and mixed flow impellers to suppress secondary flows. Based on our understanding of the fluid dynamics of the flow in the impeller, simple guidelines are developed for input specification of the inverse method in order to systematically design impellers with suppressed secondary flows and a more uniform exi
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Chen, L. L., H. Lian, Z. Liu, H. B. Chen, E. Atroshchenko, and S. P. A. Bordas. "Structural shape optimization of three dimensional acoustic problems with isogeometric boundary element methods." Computer Methods in Applied Mechanics and Engineering 355 (October 2019): 926–51. http://dx.doi.org/10.1016/j.cma.2019.06.012.

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Xiaoyan, Song, Rao Yufei, Wei Shichao, Xia Xijie, and Li Haifeng. "Three-dimensional electric field decoupling based on PSO-GA fusion under inter-dimensional coupling interference." Journal of Computational Methods in Sciences and Engineering 25, no. 2 (2024): 1714–25. https://doi.org/10.1177/14727978241302985.

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In contrast to existing methods like solving sensitivity matrices or sensor structure optimization decoupling, this paper proposes a three-dimensional electric field separation technique centered on the PSO-GA fusion algorithm, to fully utilize the rapid integration property of the particle swarm optimization algorithm and the global search capability of the genetic algorithm to improve the decoupling accuracy and optimization efficiency. The interdimensional coupling interference problem arises during the course of three-dimensional electric field measurement in space. Furthermore, a correcti
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Dissertations / Theses on the topic "Methods of three-dimensional optimization"

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Hambric, Stephen A. "Structural shape optimization of three dimensional finite element models." Thesis, Virginia Tech, 1987. http://hdl.handle.net/10919/45805.

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<p>The thesis presents a three dimensional shape optimization program which analyzes models made up of linear isoparametric elements. The goal of the program is to achieve a near uniform model stress state and thereby to minimize material volume.</p> <p> The algorithm is iterative, and performs two analyses per iteration. The first analysis is a static stress analysis of the model for one or more load cases. Based on results from the static analysis, an expansion analysis is performed. Model elements are expanded or contracted based on whether they are stressed higher or lower than a re
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Singley, Andrew M. "Heuristic solution methods for the 1-dimensional and 2-dimensional mastermind problem." [Gainesville, Fla.] : University of Florida, 2005. http://purl.fcla.edu/fcla/etd/UFE0010554.

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Ren, Xuchun. "Novel computational methods for stochastic design optimization of high-dimensional complex systems." Diss., University of Iowa, 2015. https://ir.uiowa.edu/etd/1738.

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The primary objective of this study is to develop new computational methods for robust design optimization (RDO) and reliability-based design optimization (RBDO) of high-dimensional, complex engineering systems. Four major research directions, all anchored in polynomial dimensional decomposition (PDD), have been defined to meet the objective. They involve: (1) development of new sensitivity analysis methods for RDO and RBDO; (2) development of novel optimization methods for solving RDO problems; (3) development of novel optimization methods for solving RBDO problems; and (4) development of a n
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Winkelmann, Beate Maria. "Finite dimensional optimization methods and their application to optimal control with PDE constraints /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2005. http://wwwlib.umi.com/cr/ucsd/fullcit?p3205376.

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Opdahl, Hanna Belle. "Investigation of IsoTruss® Structures in Compression Using Numerical, Dimensional, and Optimization Methods." BYU ScholarsArchive, 2020. https://scholarsarchive.byu.edu/etd/9243.

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The purpose of this research is to investigate the structural efficiency of 8-node IsoTruss structures subject to uniaxial compression using numerical, dimensional, and optimization methods. The structures analyzed herein are based on graphite/epoxy specimens that were designed for light-weight space applications, and are approximately 10 ft. (3 m) long and 0.3 lb. (0.14 kg). The principal failure modes considered are material failure, global buckling, local buckling at the bay level, and longitudinal strut buckling. Studies were performed with the following objectives: to correlate finite ele
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Acevedo, Feliz Daniel. "A framework for the perceptual optimization of multivalued multilayered two-dimensional scientific visualization methods." View abstract/electronic edition; access limited to Brown University users, 2008. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3318287.

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Schäfer, Christian. "Monte Carlo methods for sampling high-dimensional binary vectors." Phd thesis, Université Paris Dauphine - Paris IX, 2012. http://tel.archives-ouvertes.fr/tel-00767163.

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This thesis is concerned with Monte Carlo methods for sampling high-dimensional binary vectors from complex distributions of interest. If the state space is too large for exhaustive enumeration, these methods provide a mean of estimating the expected value with respect to some function of interest. Standard approaches are mostly based on random walk type Markov chain Monte Carlo, where the equilibrium distribution of the chain is the distribution of interest and its ergodic mean converges to the expected value. We propose a novel sampling algorithm based on sequential Monte Carlo methodology w
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Yi, Congrui. "Penalized methods and algorithms for high-dimensional regression in the presence of heterogeneity." Diss., University of Iowa, 2016. https://ir.uiowa.edu/etd/2299.

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In fields such as statistics, economics and biology, heterogeneity is an important topic concerning validity of data inference and discovery of hidden patterns. This thesis focuses on penalized methods for regression analysis with the presence of heterogeneity in a potentially high-dimensional setting. Two possible strategies to deal with heterogeneity are: robust regression methods that provide heterogeneity-resistant coefficient estimation, and direct detection of heterogeneity while estimating coefficients accurately in the meantime. We consider the first strategy for two robust regression
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Yan, Enxu. "Sublinear-Time Learning and Inference for High-Dimensional Models." Research Showcase @ CMU, 2018. http://repository.cmu.edu/dissertations/1207.

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Across domains, the scale of data and complexity of models have both been increasing greatly in the recent years. For many models of interest, tractable learning and inference without access to expensive computational resources have become challenging. In this thesis, we approach efficient learning and inference through the leverage of sparse structures inherent in the learning objective, which allows us to develop algorithms sublinear in the size of parameters without compromising the accuracy of models. In particular, we address the following three questions for each problem of interest: (a)
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Nikram, Elham. "Three essays on game theory and computation." Thesis, University of Exeter, 2016. http://hdl.handle.net/10871/28755.

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The results section of my thesis includes three chapters. The first two chapters are on theoretical game theory. In both chapters, by mathematical modelling and game theoretical tools, I am predicting the behaviour of the players in some real world issues. Hoteling-Downs model plays an important role in the modern political interpretations. The first chapter of this study investigates an extension of Hoteling-Downs model to have multi-dimensional strategy space and asymmetric candidates. Chapter 3 looks into the inspection game where the inspections are not the same in the series of sequential
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Books on the topic "Methods of three-dimensional optimization"

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Catalano, L. A. Two dimensional optimization of smoothing properties of multistage schemes applied to hyperbolic equations. von Karman Institute for Fluid Dynamics, 1990.

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Facchinei, Francisco. Finite-Dimensional Variational Inequalities and Complementarity Problems. Springer-Verlag New York, Inc., 2004.

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N, Tiwari S., Smith R. E, and United States. National Aeronautics and Space Administration., eds. Variational methods in design optimization and sensitivity analysis for two-dimensional Euler equations: NASA cooperative agreement NCC1-232. Institute for Computational and Applied Mechanics, Old Dominion University, 1997.

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1934-, Jameson Antony, and United States. National Aeronautics and Space Administration., eds. Control theory based airfoil design for potential flow and a finite volume discretization. National Aeronautics and Space Administration, 1995.

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1944-, Biezad Daniel J., and United States. National Aeronautics and Space Administration., eds. Subsonic wing optimization for handling qualities using ACSYNT: Final report, MS thesis : NASA grant number NCC 2-855, Cal Poly project 5339. National Aeronautics and Space Administration, 1996.

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Williams, David H. Airborne four-dimensional flight management in a time-based air traffic control environment. National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Division, 1991.

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M, Green Steven, Langley Research Center, and United States. National Aeronautics and Space Administration. Scientific and Technical Information Division., eds. Airborne four-dimensional flight management in a time-based air traffic control environment. National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Division, 1991.

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M, Green Steven, Langley Research Center, and United States. National Aeronautics and Space Administration. Scientific and Technical Information Division., eds. Airborne four-dimensional flight management in a time-based air traffic control environment. National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Division, 1991.

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M, Green Steven, Langley Research Center, and United States. National Aeronautics and Space Administration. Scientific and Technical Information Division., eds. Airborne four-dimensional flight management in a time-based air traffic control environment. National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Division, 1991.

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Baysal, Oktay. Efficient gradient-based shape optimization methodology using inviscid/viscous CFD: Summary of research report for the period of March 9, 1995 to March 8, 1997, grant# NCC-1-211. Dept. of Aerospace Engineering, College of Engineering and Technology, Old Dominion University, 1997.

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Book chapters on the topic "Methods of three-dimensional optimization"

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Mishra, Shashi Kant, and Bhagwat Ram. "One-Dimensional Optimization Methods." In Introduction to Unconstrained Optimization with R. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-0894-3_5.

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Laporte, Emmanuel, and Patrick Le Tallec. "Finite Dimensional Optimization." In Numerical Methods in Sensitivity Analysis and Shape Optimization. Birkhäuser Boston, 2003. http://dx.doi.org/10.1007/978-1-4612-0069-7_2.

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Qi, Liqun, and Defeng Sun. "Polyhedral Methods for Solving Three Index Assignment Problems." In Combinatorial Optimization. Springer US, 2000. http://dx.doi.org/10.1007/978-1-4757-3155-2_5.

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Rousselet, B. "Introduction to Shape Sensitivity Three-Dimensional and Surface Systems." In Shape and Layout Optimization of Structural Systems and Optimality Criteria Methods. Springer Vienna, 1992. http://dx.doi.org/10.1007/978-3-7091-2788-9_13.

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Cherkaev, Andrej. "Relaxation of One-Dimensional Variational Problems." In Variational Methods for Structural Optimization. Springer New York, 2000. http://dx.doi.org/10.1007/978-1-4612-1188-4_1.

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Andrei, Neculai. "Three-Term Conjugate Gradient Methods." In Nonlinear Conjugate Gradient Methods for Unconstrained Optimization. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-42950-8_9.

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Stanimirović, Ivan. "Three Direct Methods in Linear Programming." In Advances in Optimization and Linear Programming. Apple Academic Press, 2021. http://dx.doi.org/10.1201/9781003256052-3.

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Meng, Jianjun, Zeqing Yang, and Zhenrui Peng. "Path Optimization of Large-Scale Automated Three-Dimensional Garage Based on Ant Colony Algorithm." In Computational Methods in Engineering & Science. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/978-3-540-48260-4_149.

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Hamdi, Mohsen, and Ayech Benjeddou. "Robust Multi-objective Evolutionary Optimization-Based Inverse Identification of Three-Dimensional Elastic Behaviour of Multilayer Unidirectional Fibre Composites." In Computational Methods in Applied Sciences. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-44507-6_14.

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Wang, Yichen, and Dong Gao. "A Three-Dimensional Geomagnetic Matching Navigation Method Based on Particle Swarm Optimization." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-2204-7_30.

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Conference papers on the topic "Methods of three-dimensional optimization"

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Lee, Jinsu, Keehoon Hong, and Minsik Park. "Optimization method of overlapped CGHs for expanded eye-box in automotive holographic head-up display." In Digital Holography and Three-Dimensional Imaging. Optica Publishing Group, 2024. http://dx.doi.org/10.1364/dh.2024.w4a.3.

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This study integrates holographic display into automotive HUDs to tackle ghost image issues. Despite SLM limitations, using SGD optimization with a 2D beam splitter and windshield expands the eye-box, eliminating ghost images. Results achieve PSNR levels of 23-26dB, demonstrating holographic HUD potential in cars without treated windshields.
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Zhang, Yunping, and Edmund Y. Lam. "Overcoming deterministic perturbations in physics-informed holographic reconstruction through joint optimization." In Digital Holography and Three-Dimensional Imaging. Optica Publishing Group, 2024. http://dx.doi.org/10.1364/dh.2024.tu1a.3.

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We propose a novel holographic imaging method that jointly optimizes complex-valued magnitude and mismatched physical parameters to address degraded and erroneous reconstructions caused by physical perturbations.
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Takahashi, Youhei, Satoshi Hasegawa, and Yoshio Hayasaki. "Second-harmonic optimization method of a hologram." In Digital Holography and Three-Dimensional Imaging. OSA, 2010. http://dx.doi.org/10.1364/dh.2010.dmb4.

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Blinder, David, Fan Wang, Peter Schelkens, Takashi Kakue, and Tomoyoshi Shimobaba. "Joint color optimization for holographic displays." In Digital Holography and Three-Dimensional Imaging. Optica Publishing Group, 2023. http://dx.doi.org/10.1364/dh.2023.hw4c.6.

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Color holographic displays usually independently modulate and multiplex light for three wavelengths. We propose a novel algorithm for jointly encoding a single extended- phase SLM pattern creating color holograms surpassing the quality of the reference method.
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Wang, Haibei, Ping Su, and Jianshe Ma. "The Optimization of Random Phase in 3D-CGHs Based on Depth Information." In Digital Holography and Three-Dimensional Imaging. Optica Publishing Group, 2022. http://dx.doi.org/10.1364/dh.2022.w5a.27.

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A new method is proposed to reduce speckle noise by optimizing the random phase of 3D-CGHs with the angular spectrum algorithm based on depth information. Simulation results show that the method can suppress the reconstructed noise.
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Shaji, Athira, and M. K. Sheeja. "ADMM Based Regularized Optimization for Reconstruction of Digital In-line Holography." In Digital Holography and Three-Dimensional Imaging. Optica Publishing Group, 2022. http://dx.doi.org/10.1364/dh.2022.tu2a.7.

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Compressed sensing is effective in twin image removal of in-line holograms, but has slower convergence and higher computational time. Proposed method suppresses twin images by solving an inverse problem using ADMM and offers better convergence.
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Xia, Xinxing, Furong Yang, Weisen Wang, Xinghua Shui, Yunqing Guan, and Yingjie Yu. "Hardware-in-the-loop Optimization for Hologram Rendering in Holographic Near-eye Display." In Digital Holography and Three-Dimensional Imaging. Optica Publishing Group, 2022. http://dx.doi.org/10.1364/dh.2022.w5a.46.

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We propose a novel deep-learning-based hologram generation method with the end-to-end optimization with the combination of all optical devices. Experiments have been carried out to verify its feasibility.
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Yang, Dong-Yol, Seok-Ryul Lee, and Kyung-Jin Kim. "Design Optimization for Three-Dimensional Extrusion Processes." In MATERIALS PROCESSING AND DESIGN; Modeling, Simulation and Applications; NUMIFORM '07; Proceedings of the 9th International Conference on Numerical Methods in Industrial Forming Processes. AIP, 2007. http://dx.doi.org/10.1063/1.2740824.

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Kazakovtsev, Lev A. "System for Automatic Grouping of Metadata of Three-Dimensional Models." In International Workshop “Hybrid methods of modeling and optimization in complex systems”. European Publisher, 2023. http://dx.doi.org/10.15405/epct.23021.42.

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Min, Kyosik, Dabin Min, and Jae-Hyeung Park. "Quality enhancement of Wigner inverse transform-based light field to computer-generated hologram by optimizing carrier wave." In Digital Holography and Three-Dimensional Imaging. Optica Publishing Group, 2023. http://dx.doi.org/10.1364/dh.2023.hm1d.3.

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We propose a novel method to ensure high reconstruction quality of the CGHs by using optimized carrier waves. The proposed method pre-optimizes the carrier waves for certain distances and uses them for synthesizing CGHs of various 3D objects, without requiring contents-wise training and optimization. The proposed method is verified with simulations.
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Reports on the topic "Methods of three-dimensional optimization"

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Pasupuleti, Murali Krishna. Phase Transitions in High-Dimensional Learning: Understanding the Scaling Limits of Efficient Algorithms. National Education Services, 2025. https://doi.org/10.62311/nesx/rr1125.

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Abstract: High-dimensional learning models exhibit phase transitions, where small changes in model complexity, data size, or optimization dynamics lead to abrupt shifts in generalization, efficiency, and computational feasibility. Understanding these transitions is crucial for scaling modern machine learning algorithms and identifying critical thresholds in optimization and generalization performance. This research explores the role of high-dimensional probability, random matrix theory, and statistical physics in analyzing phase transitions in neural networks, kernel methods, and convex vs. no
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Pasupuleti, Murali Krishna. Stochastic Computation for AI: Bayesian Inference, Uncertainty, and Optimization. National Education Services, 2025. https://doi.org/10.62311/nesx/rriv325.

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Abstract: Stochastic computation is a fundamental approach in artificial intelligence (AI) that enables probabilistic reasoning, uncertainty quantification, and robust decision-making in complex environments. This research explores the theoretical foundations, computational techniques, and real-world applications of stochastic methods, focusing on Bayesian inference, Monte Carlo methods, stochastic optimization, and uncertainty-aware AI models. Key topics include probabilistic graphical models, Markov Chain Monte Carlo (MCMC), variational inference, stochastic gradient descent (SGD), and Bayes
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Pasupuleti, Murali Krishna. Quantum-Enhanced Machine Learning: Harnessing Quantum Computing for Next-Generation AI Systems. National Education Services, 2025. https://doi.org/10.62311/nesx/rrv125.

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Abstract Quantum-enhanced machine learning (QML) represents a paradigm shift in artificial intelligence by integrating quantum computing principles to solve complex computational problems more efficiently than classical methods. By leveraging quantum superposition, entanglement, and parallelism, QML has the potential to accelerate deep learning training, optimize combinatorial problems, and enhance feature selection in high-dimensional spaces. This research explores foundational quantum computing concepts relevant to AI, including quantum circuits, variational quantum algorithms, and quantum k
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Hopmann, Christian, Christoph Zimmermann, Daniel C. Fritsche, et al. Design of an injection mold with local placement of heating coatings for warpage compensation. Universidad de los Andes, 2024. https://doi.org/10.51573/andes.pps39.gs.im.1.

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The influence of the thermal injection mold design crucially affects the geometric precision of injection molded parts. However, the adjustability of the heat flux distribution established with the conventionally used cooling channels is limited and cannot cover the vari able cooling demand. The proposed approach of using heating coatings on the cavity surface to manipulate the part’s cooling rate shows that it may be advantageous, due to the close and localized application to the part. A simulative optimization routine determines the necessary position and surface power of the heating coating
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Williamson, Chatt C., and Yansen Wang. Optimization of a Three-Dimensional Diagnostic Flow Solver. Defense Technical Information Center, 2010. http://dx.doi.org/10.21236/ada564452.

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Zabarankin, Michael. Semi-Analytical Approach to Three-Dimensional Shape Optimization Problems. Defense Technical Information Center, 2008. http://dx.doi.org/10.21236/ada482147.

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Cao, Yusong, William W. Schultz, and Robert F. Beck. Three-Dimensional Desingularized Boundary Integral Methods for Potential Problems. Defense Technical Information Center, 1990. http://dx.doi.org/10.21236/ada251151.

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Lewis, E. E. Variational nodal transport methods for hexagonal and three-dimensional geometries. Office of Scientific and Technical Information (OSTI), 1992. http://dx.doi.org/10.2172/7152709.

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Ruelas, Samantha. Optimization of PDMS Photoresin for Three-Dimensional Printng via Projection Micro-Stereolithography. Office of Scientific and Technical Information (OSTI), 2018. http://dx.doi.org/10.2172/1460080.

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Yang, David, Arash Khosravifar, Diane Moug, and Avinash Unnikrishnan. Framework and Methodology for Risk-Based Bridge and Tunnel Asset Management: Objective Risk Assessment and Network Level Evaluation. Portland State University, 2024. https://doi.org/10.15760/cee-reports.01.

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Abstract:
This report presents the results of the project on establishing a general framework and methodology for risk-based bridge and tunnel asset management. The research was carried out at Portland State University in collaboration with engineers and officials at Oregon Department of Transportation (ODOT) and Federal Highway Administration (FHWA). The primary goal of the research is to achieve risk-based transportation asset management based on (a) objective and consistent risk assessment and (b) effective prioritization and optimization of intervention strategies. Volume I of this report presents m
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