Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Simulation optimization”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Optimizing Muscle Parameters in Musculoskeletal Modeling Using Monte Carlo Simulations

Astronauts assigned to long-duration missions experience bone and muscle atrophy in the lower limbs. The use of musculoskeletal simulation software has become a useful tool for modeling joint and muscle forces during human activity in reduced gravity as access to direct experimentation is limited. Knowledge of muscle and joint loads can better inform the design of exercise protocols and exercise countermeasure equipment. In this study, the LifeModeler(TM) (San Clemente, CA) biomechanics simulation software was used to model a squat exercise. The initial model using default parameters yielded physiologically reasonable hip-joint forces. However, no activation was predicted in some large muscles such as rectus femoris, which have been shown to be active in 1-g performance of the activity. Parametric testing was conducted using Monte Carlo methods and combinatorial reduction to find a muscle parameter set that more closely matched physiologically observed activation patterns during the squat exercise. Peak hip joint force using the default parameters was 2.96 times body weight (BW) and increased to 3.21 BW in an optimized, feature-selected test case. The rectus femoris was predicted to peak at 60.1% activation following muscle recruitment optimization, compared to 19.2% activation with default parameters. These results indicate the critical role that muscle parameters play in joint force estimation and the need for exploration of the solution space to achieve physiologically realistic muscle activation.

Hanson, Andrea↗
DOE OSTI2025

Incident beam optics optimization for the single crystal neutron diffractometer Pioneer with a polarized beam option

Pioneer, a next-generation single-crystal neutron diffractometer, is under development for Oak Ridge National Laboratory’s Second Target Station. Designed to address a wide range of scientific questions, Pioneer will deliver homogeneous neutron beams with customizable size and divergence and provide a polarized beam option. This article introduces its incident beam optics, highlighting the optimization methodology and the simulated performance. Pioneer will utilize a modified elliptical-straight guide for neutron transport and deploy slit packages and insertable apertures to control beam size and divergence. The optimized guide geometry matches the optimal-and-full-sample-illumination condition, and the beam control system effectively filters out unwanted neutrons while preserving the desired ones. In addition, we have found that polygon-approximated guides provide satisfactory transport efficiency and beam homogeneity, eliminating the need for truly curved guides. Further, to enhance neutronics performance and reduce cost, the coatings of supermirror elements are individually optimized to the lowest half-integer m-values that are sufficient to deliver the desired neutrons. After evaluating polarizing V-cavities and 3 He spin filters over the default polarized wavelength band of 1.2–5.5 Å, we selected a translatable multichannel polarizing V-cavity as the incident beam polarizer. Strategically placed at a location where the beam divergence is low and a large in-guide gap has negligible impact on transport efficiency, the optimized V-cavity achieves an average P 2 T of ~35%.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Enhanced Performance Fast Reactors with Engineered Passive Safety Systems

This report summarizes the work and results of NEUP Project #15-8251, "Enhanced Performance Fast Reactors with Engineered Passive Safety System," performed from 2015-2018 at UC Berkeley and Argonne National Laboratory. This project concerns the incorporation of a novel engineered passive safety system, called the Autonomous Reactivity Control (ARC) system, into Sodium-cooled Fast Reactors (SFRs) to improve their transient and economic performance. The first part of this project consisted of fleshing out the basic principles and the manufacturing process for an SFR fuel assembly with the ARC system installed, with the details provided in high-quality, step-by-step CAD drawings. Once the detailed design is laid out, high-fidelity simulations were performed to optimize the dimensions of important ARC system components and to quantify the standalone time-response of ARC systems in a typical SFR environment. These high-fidelity simulations were used to create reduced-order models of ARC system response which could be incorporated into the SAS4A/SASSYS-1 whole-core transient models. In order to accurately account for the time-response of ARC systems in whole-core transient simulations, modifications were made to the SAS4A/SASSYS-1 transient code. These new capabilities were tested and incorporated into the production version of the code, and have been used extensively in this analysis. Before performing whole-core transient calculations, the two reference cores selected for this study to cover a wide design space were simulated and characterized. The two reference cores, (1) a medium-sized oxide-fueled Advanced Burner Reactor and (2) a large metal-fueled Breed-and-Burn core, challenge conventional means of achieving passive safety. Because the two cores vary substantially, simulating the ARC system in both allows for conclusions to be drawn about the applicability of ARC systems in different SFRs. Once both cores were fully characterized, transient calculations were performed to understand the complicated interplay between the ARC system and other inherent reactivity feedback mechanisms. By performing parametric studies of the transient behavior, ARC system designs that best improve transient performance in each core were identified. Once transient improvements were established, the transient calculations were extended to improve reactor economics through design modifications. Upon establishing the potential benefits of ARC system inclusion, the study examines the negative neutronic implications of incorporating ARC systems into the reference cores. The study concludes by discussing a number of knowledge gaps that exist which may have important implications for ARC system implementation. Ultimately, the results of this project indicate that ARC systems may provide an effective means to improve transient performance in certain types of systems. The transient simulations in the oxide Advanced Burner Reactor showed that significant margin to coolant boiling and fuel melting could be gained through the use of a properly designed ARC system, thus improving inherent safety. While oscillatory behavior was induced in the transient response for certain combinations of ARC system parameters, the oscillation-free design space that can be effectively used to improve performance was found to be large, and the additional margin was demonstrated to allow economical improvements to the core design. Conversely, difficulties were encountered in the Breed-and-Burn core due to fundamental aspects of the core design. The combination of a particularly strong positive coolant void feedback and the use of metallic fuel allowed for diverging oscillations to manifest in response to certain transient initiators, and in the end it was found that the current ARC system design could not simultaneously enable passive safety in all transients examined. In order for complete passive safety to be achieved, a mechanism for slowing the reverse actuation of ARC systems is necessary. Regardless, the standard ARC system was able to improve the performance of two out of the three examined transients by increasing the margin to boiling in Loss of Heat Sink transients and avoiding boiling in Transient Overpower accidents. Additionally, no significant barriers to implementation were found, although the issue of tritium production should be closely monitored in any core incorporating ARC systems. Still, a number of technology gaps exist, and these are discussed at the conclusion of the report to recommend directions for future work.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Design-Space Exploration for Inverse-Design of Wind Turbine Blades Using Data-Driven Methods

The state-of-the-practice aerodynamic design methods for wind turbine blades is typically based on Blade-Element Momentum (BEM) theory using a pre-designed frozen family of airfoils. The airfoils are themselves typically designed using panel methods. The design of the next-generation of large flexible rotors will need to capture the non-linear aerodynamics and three-dimensional flow to reduce the levelized cost of wind energy. Data-driven methods for aerodynamic design using data generated by computational fluid dynamics offer an attractive alternative to BEM-based methods that captures the non-linear aerodynamics of the component airfoils as well as the root and tip sections. In this work, we develop and demonstrate a framework to "smartly" explore the relevant design space in combination with an appropriate automated CFD pipeline to evaluate the aerodynamics of each design. The design-space exploration framework uses appropriate perturbations to the airfoil shape and induction profile from a baseline shape in combination with the inverse-design using BEM. The resulting designs are evaluated using an automated CFD pipeline using the in-house CFD solver framework "Mercury". We perform verification and validation to establish the capability of the Mercury framework to predict the aerodynamic performance of wind turbines. The CFD simulation of the perturbed blade shapes are optimized to restart from the converged baseline simulation to reduce the computational time. Finally, we demonstrate the design-space exploration technique for the design of the outboard section and the full rotor using perturbations to the shape and operating conditions of the NREL 5-MW turbine.

aerodynamic design methods↗
DOE OSTI2024

Optimization Studies of Radiation Shielding for PIP-II Project at Fermilab

The Proton Improvement Plan-II (PIP-II) at Fermilab represents a significant advancement in the quest to answer some of the most profound questions about our universe using the world's most intense high-energy neutrino beam. The project requires the construction of a new addition to the Fermilab accelerator complex – an 800-MeV high-intensity superconducting linear accelerator. Ensuring the safety and regulatory compliance of this ambitious project is paramount, necessitating thorough dose rate assessments under both normal operational and accidental scenarios to align with the Fermilab Radiological Control Manual (FRCM) standards. Our approach included a shielding optimization used for the simulations with the Monte Carlo code MARS [1,2,3] to incorporate new magnet and collimator designs, essential for reflecting the current state of PIP-II infrastructure. The implementation of high-resolution detector planes, despite their computational demands, enabled us to gather detailed radiation field data crucial for optimizing shielding configurations. To overcome the significant computational demands, we developed a branching code that drastically reduced simulation runtimes while maintaining statistical integrity. This was achieved through geometry splitting and the application of Russian Roulette techniques, tailored to prioritize regions of interest based on predefined importances and weight limits.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Optimization Studies of Radiation Shielding for PIP-II Project at Fermilab

The Proton Improvement Plan-II (PIP-II) at Fermilab represents a significant advancement in the quest to answer some of the most profound questions about our universe using the world's most intense high-energy neutrino beam. The project requires the construction of a new addition to the Fermilab accelerator complex – an 800-MeV high-intensity superconducting linear accelerator. Ensuring the safety and regulatory compliance of this ambitious project is paramount, necessitating thorough dose rate assessments under both normal operational and accidental scenarios to align with the Fermilab Radiological Control Manual (FRCM) standards. Our approach included a shielding optimization used for the simulations with the Monte Carlo code MARS [1,2,3] to incorporate new magnet and collimator designs, essential for reflecting the current state of PIP-II infrastructure. The implementation of high-resolution detector planes, despite their computational demands, enabled us to gather detailed radiation field data crucial for optimizing shielding configurations. To overcome the significant computational demands, we developed a branching code that drastically reduced simulation runtimes while maintaining statistical integrity. This was achieved through geometry splitting and the application of Russian Roulette techniques, tailored to prioritize regions of interest based on predefined importances and weight limits.

Makovec, Alajos↗
DOE OSTI2026

Consequential improvement acquisition function for efficient multi-fidelity Bayesian optimization

Abstract Surrogate-based Bayesian optimization has been widely applied in design optimization to increase sampling efficiency. However, the cost for each evaluation of the objective function can still be very high when physical experiments or large-scale simulations are involved. Multi-fidelity Bayesian optimization is the new approach to further improve the sampling efficiency by reducing the number of expensive samples at the highest fidelity level and supplementing them with less expensive ones at low-fidelity levels. In this paper, a new consequential improvement (CI) acquisition function is proposed to allow for the simultaneous selection of the solution and the fidelity level in problems with a known hierarchy of fidelity levels. The new CI acquisition function incorporates the consequential effectiveness of objective improvement with the considerations of cost, accuracy, and validity differences between high- and low-fidelity samples in engineering practice. The new method of multi-fidelity Bayesian optimization based on the CI is demonstrated with several analytical and simulation-based design examples. In the simulation-based design optimization example, the results show that the CI acquisition function has a decisive advantage in the sampling efficiency over the other methods of multi-fidelity Bayesian optimization with simultaneous selection. The results indicate that the proposed method is particularly advantageous in solving high-dimensional problems and when large cost ratios between high- and low-fidelity evaluations exist and high-fidelity validation is mandatory. Furthermore, the method robustly avoids the prevalent issue of over sampling at low-fidelity levels.

Aydogdu, Ibrahim [Georgia Institute of Technology,↗
NASA NTRS1996

ATTDES: An Expert System for Satellite Attitude Determination and Control

The design, analysis, and flight operations of satellite attitude determintion and attitude control systems require extensive mathematical formulations, optimization studies, and computer simulation. This is best done by an analyst with extensive education and experience. The development of programs such as ATTDES permit the use of advanced techniques by those with less experience. Typical tasks include the mission analysis to select stabilization and damping schemes, attitude determination sensors and algorithms, and control system designs to meet program requirements. ATTDES is a system that includes all of these activities, including high fidelity orbit environment models that can be used for preliminary analysis, parameter selection, stabilization schemes, the development of estimators covariance analyses, and optimization, and can support ongoing orbit activities. The modification of existing simulations to model new configurations for these purposes can be an expensive, time consuming activity that becomes a pacing item in the development and operation of such new systems. The use of an integrated tool such as ATTDES significantly reduces the effort and time required for these tasks.

Mackison, Donald L.↗
DOE OSTI2021

Selective Enhancement of Spectroscopic Features by Quantum Optimal Control

Tailored light can be used to steer atomic motions into selected quantum pathways. In optimal control theory (OCT), the target is usually expressed in terms of the molecular wave function, a quantity that is not directly observable in experiment. In this study, we present simulations using OCT that optimize the spectroscopic signal itself. By shaping the optical pump, the x-ray stimulated Raman signal, which occurs solely during the passage through conical intersections, is temporally controlled and amplified by up to 2 orders of magnitude. This enhancement can be crucial in order to bring small coherence-based signatures above the detectable threshold. Our approach is applicable to any signal that depends on the expectation value of a positive definite operator.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Exploration of superconducting multi-mode cavity architectures for quantum computing

Superconducting radio-frequency (SRF) cavities coupled to transmon circuits have proven to be a promising platform for building high-coherence quantum information processors. An essential aspect of this realization involves designing high quality factor three-dimensional superconducting cavities to extend the lifetime of quantum systems. To increase the computational capability of this architecture, we are exploring a multimode approach. This paper presents the design optimization process of a multi-cell SRF cavity to perform quantum computation based on an existing design developed in the scope of particle accelerator technology. We perform parametric electromagnetic simulations to evaluate and optimize the design. In particular, we focus on the analysis of the interaction between a nonlinear superconducting circuit known as the transmon and the cavity. This parametric design optimization is structured to serve as a blueprint for future studies on similar systems.

Reineri, Alessandro↗
DOE OSTI2022

A Hybrid Method for Tensor Decompositions that Leverages Stochastic and Deterministic Optimization

In this paper, we propose a hybrid method that uses stochastic and deterministic search to compute the maximum likelihood estimator of a low-rank count tensor with Poisson loss via state-of-theart local methods. Our approach is inspired by Simulated Annealing for global optimization and allows for fine-grain parameter tuning as well as adaptive updates to algorithm parameters. We present numerical results that indicate our hybrid approach can compute better approximations to the maximum likelihood estimator with less computation than the state-of-the-art methods by themselves.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2010

Optimizing Medical Kits for Space Flight

The Integrated Medical Model (IMM) uses Monte Carlo methodologies to predict the occurrence of medical events, their mitigation, and the resources required during space flight. The model includes two modules that utilize output from a single model simulation to identify an optimized medical kit for a specified mission scenario. This poster describes two flexible optimization routines built into SAS 9.1. The first routine utilizes a systematic process of elimination to maximize (or minimize) outcomes subject to attribute constraints. The second routine uses a search and mutate approach to minimize medical kit attributes given a set of outcome constraints. There are currently 273 unique resources identified that are used to treat at least one of 83 medical conditions currently in the model.

Minard, Charles G.↗
NASA NTRS1993

Optimization of blade arrangement in a randomly mistuned cascade using simulated annealing

This paper presents preliminary results of an investigation on mistuning of bladed-disk assemblies aimed at capturing the benefits of mistuning on stability, while at the same time, minimizing the adverse effects on response by solving the following problem: given a set of N turbine blades, each being a small random perturbation of the same nominal blade, determine the best arrangement of the N blades in a mistuned cascade with regard to aeroelastic response. In the studies reported here, mistuning of the blades is restricted to small differences in torsional stiffness. The large combinatorial optimization problem of seeking the best arrangement by blade exchanges is solved using a simulated annealing algorithm.

Thompson, Edward A.↗
DOE OSTI2021

Deep learning simulations of the microwave sky

Here we present 500 high-resolution, full-sky millimeter-wave deep learning (DL) simulations that include lensed CMB maps and correlated foreground components. We find that these MillimeterDL simulations can reproduce a wide range of non-Gaussian summary statistics matching the input training simulations, while only being optimized to match the power spectra. The procedure we develop in this work enables the capability to mass produce independent full-sky realizations from a single expensive full-sky simulation, when ordinarily the latter would not provide enough training data. We also circumvent a common limitation of high-resolution DL simulations that they be confined to small sky areas, often due to memory or GPU issues; we do this by developing a “stitching” procedure that can recover the large-scale, high-order statistics and avoid discontinuities or repeated features in the maps. In addition, since our network takes as input a full-sky lensing convergence map, it can in principle take a full-sky lensing convergence map from any large-scale structure (LSS) simulation and generate the corresponding lensed CMB and correlated foreground components at millimeter wavelengths; this is especially useful in the current era of combining results from both CMB and LSS surveys, which require a common set of simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1999

Nanoporous Silica Thermal Insulation for Space Shuttle Cryogenic Tanks: A Case Study

Nanoporous silica (with typical 10-50 nm porous radii) has been benchmarked for thermal insulators capable of maintaining a 150 K/cm temperature gradient. For cryogenic use in aerospace applications, the combined features for low-density, high thermal insulation factors, and low temperature compatibility are demonstrated in a prototype sandwich structure between two propulsion tanks. Theoretical modelling based on a nanoscale fractal structure suggest that the thermal conductivity scales proportionally (exponent, 1.7) with the material density-lower density increases the thermal insulation rating. Computer simulations, however, support the optimization tradeoff between material strength (Young moduli, proportional to density with exponent, 3.7), the characteristic (colloidal silica, less than 5 nm) particle size, and the thermal rating. The results of these simulations indicate that as nanosized particles are incorporated into the silica backbone, the resulting physical properties will be tailored by the smallest characteristic length and their fractal interconnections (dimension and fractal size). The application specifies a prototype panel which takes advantage of the processing flexibility inherent in sol-gel chemistry.

Noever, David A.↗
DOE OSTI2021

White Box Access to Quantum Testbeds for Co-Design

At Lawrence Livermore National Laboratory (LLNL), we operate and maintain the Quantum Device and Integration Testbed (QuDIT) facility, a small quantum testbed that supports about 10 active research teams (including our own) and over 50 internal and external collaborators. This testbed is designed to give remote white box access to users for research, training, and outreach. A guiding principle behind the development of our testbed infrastructure, software and user interfaces is to empower users to perform experiments at the cutting edge of quantum information science at any level of abstraction, from materials studies, device physics and control and characterization techniques to algorithm development and quantum operating system design. Our testbed targets a multilevel quantum system (qudit) to expand the accessible Hilbert space of a simple-to-manufacture quantum device and focuses on quantum simulation, typically implemented through custom gates designed with quantum optimal control methods, rather than on a universal computing framework with a fixed gate set. We leverage the Lab’s high-performance computing (HPC) program and related expertise to simulate quantum systems, develop hybrid algorithms, and generate gates optimized for given simulations. Additionally, we have adopted a co-design philosophy from the HPC community in designing new hardware, so that the systems we develop are optimized for the specific physics simulations we plan to use them for.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Data-Driven Co-optimization of Energy Efficiency and Indoor Environmental Quality in Commercial Buildings

In this paper, we use publicly available data of a highly instrumented building to estimate how zonal temperature and carbon dioxide (CO2) concentration are related to some key operational and environmental measurements. Subsequently, we have developed, simulated, and evaluated an optimization framework for minimizing the energy consumption of the central heating, ventilation and air conditioning (HVAC) unit while meeting zonal temperature and indoor air quality (IAQ) standards. Finally, we have evaluated the achievable energy savings for our proposed approach as compared to a baseline approach and reported significant savings potential.

Naqvi, Syed Ahsan Raza↗