Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Design 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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Analysis and optimization of seismic monitoring networks with Bayesian optimal experimental design

SUMMARY Monitoring networks increasingly aim to assimilate data from a large number of diverse sensors covering many sensing modalities. Bayesian optimal experimental design (OED) seeks to identify data, sensor configurations or experiments which can optimally reduce uncertainty and hence increase the performance of a monitoring network. Information theory guides OED by formulating the choice of experiment or sensor placement as an optimization problem that maximizes the expected information gain (EIG) about quantities of interest given prior knowledge and models of expected observation data. Therefore, within the context of seismo-acoustic monitoring, we can use Bayesian OED to configure sensor networks by choosing sensor locations, types and fidelity in order to improve our ability to identify and locate seismic sources. In this work, we develop the framework necessary to use Bayesian OED to optimize a sensor network’s ability to locate seismic events from arrival time data of detected seismic phases at the regional-scale. This framework requires five elements: (i) A likelihood function that describes the distribution of detection and traveltime data from the sensor network, (ii) A prior distribution that describes a priori belief about seismic events, (iii) A Bayesian solver that uses a prior and likelihood to identify the posterior distribution of seismic events given the data, (iv) An algorithm to compute EIG about seismic events over a data set of hypothetical prior events, (v) An optimizer that finds a sensor network which maximizes EIG. Once we have developed this framework, we explore many relevant questions to monitoring such as: how to trade off sensor fidelity and earth model uncertainty; how sensor types, number and locations influence uncertainty; and how prior models and constraints influence sensor placement.

58 GEOSCIENCES↗
DOE OSTI2026

Optimized Tandem Catalyst Patterning for CO 2 Reduction Flow Reactors

Tandem catalysis involves two or more catalysts arranged in proximity within a single reaction vessel, with the aim of synergistically aligning the catalysts’ reaction pathways to maximize overall system performance. This study presents a proof of concept showing the integration of continuum transport modeling with design optimization in a simplified two-dimensional flow reactor setup for electrochemical CO 2 reduction. Ag catalysts provide the CO 2 ⟶ CO reaction capability, and Cu catalysts provide the CO ⟶ high-value products reaction capability. Given a set of input parameters, the optimization algorithm uses adjoint methods to modify the Ag/Cu surface patterning in order to maximize the current density toward high-value products, such as ethylene. The optimized designs yield significant performance enhancement especially at more negative applied voltages (i.e., stronger surface reactions) and for larger numbers of patterning sections. For an applied voltage of −1.7 V vs. SHE, the 12-section optimized design increases the current density toward ethylene by up to 65% compared to the unoptimized 2-section design. For the optimized cases, observed differences in the production and consumption of CO (the key intermediate species) and minimized zones of low CO reactant surface concentration on Cu sections explain the improved reactor performance.

CO2 reduction↗
DOE OSTI2017

Optimal Experimental Design Using a Consistent Bayesian Approach

We consider the utilization of a computational model to guide the optimal acquisition of experimental data to inform the stochastic description of model input parameters. Our formulation is based on the recently developed consistent Bayesian approach for solving stochastic inverse problems, which seeks a posterior probability density that is consistent with the model and the data in the sense that the push-forward of the posterior (through the computational model) matches the observed density on the observations almost everywhere. Given a set of potential observations, our optimal experimental design (OED) seeks the observation, or set of observations, that maximizes the expected information gain from the prior probability density on the model parameters. We discuss the characterization of the space of observed densities and a computationally efficient approach for rescaling observed densities to satisfy the fundamental assumptions of the consistent Bayesian approach. Finally, numerical results are presented to compare our approach with existing OED methodologies using the classical/statistical Bayesian approach and to demonstrate our OED on a set of representative partial differential equations (PDE)-based models.

42 ENGINEERING↗
DOE OSTI2021

Planar Transformer With Asymmetric Integrated Leakage Inductance Using Horizontal Air Gap

This article presents a novel planar-based transformer winding and core structure with controllable leakage inductance generation for integrated magnetics applications. As a result of limitations in integrated magnetics from the literature, a new approach is proposed utilizing semi-interleaved windings and controllable leakage via a leakage flux core leg featuring a horizontal air gap. Here, the proposed transformer design is analyzed via detailed reluctance modeling to determine closed-form equations for the magnetizing and asymmetrically distributed leakage inductances. Next, a genetic-algorithm-based multiobjective design optimization problem is developed, seeking to minimize the core and winding losses of the proposed transformer subject to a set of parametric and geometric constraints in a dc-ac dual-active-bridge topology for microinverter applications. The optimization was extended to include other integrated magnetic structures from the literature, where it is determined that the proposed transformer is superior from the perspectives of efficiency, footprint area, and parasitic capacitance. Based on the results of the optimization analysis, two designs with theoretical transformer California Energy Commission (CEC) efficiency drops (i.e., CEC efficiency reduction specifically due to the transformer loss mechanisms) of 1.19% and 0.83% were fabricated and evaluated for electrical and thermal performance in the proposed 40 V, 400 W microinverter.

42 ENGINEERING↗
DOE OSTI2015

Design and optimization of microbolometer multilayer optical cavity

Microbolometers are the most widely used detectors in long-wave infrared uncooled thermal imagers. An optical cavity is required within a microbolometer structure to increase its optical absorption. In this work we present a detailed study on the design and optimization of a microbolometer optical cavity using Essential-Macleod package. In the simulations, the cavity is considered as thin film multi-layers that form cascaded Fabry-Perot optical cavities. In the design phase, the layers structures are selected including materials and initial thickness. The absorbing layers are chosen to be vanadium-pentoxide (V{sub 2}O{sub 5}) and titanium (Ti). In the optimization phase, the designed layer thicknesses are varied to maximize optical absorption within the absorbing layers. The simulations show that Ti layer absorption dominates over V{sub 2}O{sub 5} layer. Also, the optimization proves that the air-gap cavity thickness is not simply quarter-wavelength because of the complex cascaded Fabry-Perot structure. The optimized air-gap thickness here is ≈3.5 µm at 10.6µm wavelength.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Fuel Behavior Implications of Reactor Design Choices in Pressurized Water SMRs

Small pressurized water reactors (PWRs) can feature boron free operation, natural circulation mode, reduced height assemblies and/or long refueling cycles. This paper attempts to explore core design optimization for each of these design evolutions. In consequence, five core design layouts are developed incorporating boron free operation with continuous control rods insertion, natural circulation with low burnup/low power density design, natural circulation with high burnup/low power density design, forced circulation with standard core power density design, and forced circulation with high power density design. These cores’ performance is compared to a standard 4-loop PWR. The design process aims to improve the fuel cycle cost under safety constraints through core design optimization using CASMO4E/SIMULATE3 reactor physics codes and FRAPCON4.1 fuel performance assessment tool. Core modeling assumes standard 17x17 PWR fuel assemblies loaded with low enriched uranium (LEU) up to 5wt% or LEU+ (i.e., below 10wt% enrichment) pellets with gadolinium oxide (Gd2O3) as the burnable poison. Satisfactory core and fuel performances are obtained for all the designed cores under steady state and considered overpower transients. For low power density operation, long cycle lengths are achieved reaching a 2.5- and a 5-year cycles and peak rod-average burnup is pushed to 83 MWd/kgU. Other cycle lengths are maintained at 18 months. Boron free operation exhibits the ability to achieve longer cycle lengths at the cost of higher peaking factors leading to high local power and fuel temperatures which prevents sizable power uprates and is deemed uneconomical. Fuel assembly height reduction allows coolant velocity retrofit which enables higher core power density without violating structural integrity of the fuel assembly. As a result, a core power density of 123 kW/l is reached where total cladding hoop strain becomes the limiting parameter.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Optimal experimental design: Formulations and computations

Questions of ‘how best to acquire data’ are essential to modelling and prediction in the natural and social sciences, engineering applications, and beyond. Optimal experimental design (OED) formalizes these questions and creates computational methods to answer them. This article presents a systematic survey of modern OED, from its foundations in classical design theory to current research involving OED for complex models. We begin by reviewing criteria used to formulate an OED problem and thus to encode the goal of performing an experiment. We emphasize the flexibility of the Bayesian and decision-theoretic approach, which encompasses information-based criteria that are well-suited to nonlinear and non-Gaussian statistical models. We then discuss methods for estimating or bounding the values of these design criteria; this endeavour can be quite challenging due to strong nonlinearities, high parameter dimension, large per-sample costs, or settings where the model is implicit. A complementary set of computational issues involves optimization methods used to find a design; we discuss such methods in the discrete (combinatorial) setting of observation selection and in settings where an exact design can be continuously parametrized. Finally we present emerging methods for sequential OED that build non-myopic design policies, rather than explicit designs; these methods naturally adapt to the outcomes of past experiments in proposing new experiments, while seeking coordination among all experiments to be performed. Throughout, we highlight important open questions and challenges.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Design and Optimization of Processes for Recovering Rare Earth Elements from End-of-Life Hard Disk Drives

In this poster, we first provide motivation for why rare earth elements as rare earth permanent magnets (REPM) are increasing in demand. We then highlight some of the recent work that has been done by several national labs (National Renewable Energy Laboratory (NREL), Environmental Protection Agency (EPA), Critical Minerals Institute (CMI)) on recycling rare earth elements from end-of-life hard disk drives (EOL). Then, we mention our long-term plan to design a feedstock agnostic process to recover rare earth elements as rare earth oxides from many different EOL products at once. Next, we discuss how we quantified the rare earth elements available for recycling from EOL hard disk drives from consumer desktops and laptops. We then discuss how we used superstructure optimization to design the optimal pathway. The proposed superstructure was modeled as a MILP optimization problem, selecting the net present value as the objective function. Costing data from the literature was used to inform this model whenever possible. However, due to the novelty of this research area, data were often unavailable, thus requiring the generation of flowsheets implemented in Aspen Plus.

Laliwala, Chris↗
DOE OSTI2014

Optimal beam design on intensity-modulated radiation therapy with simultaneous integrated boost in nasopharyngeal cancer

This study aims to determine the optimal beam design among various combinations of field numbers and beam trajectories for intensity-modulated radiation therapy (IMRT) with simultaneous integrated boost (SIB) technique for the treatment of nasopharyngeal cancer (NPC). We used 10 fields with gantry angles of 155°, 130°, 75°, 25°, 0° L, 0° R, 335°, 285°, 230°, and 205° denoted as F10. To decrease doses in the spinal cord, the F10 technique was designed by featuring 2 pairs of split-opposed beam fields at 155° to 335° and 205° to 25°, as well as one pair of manually split beam fields at 0°. The F10 technique was compared with 4 other common field arrangements: F7E, 7 fields with 50° equally spaced gantry angles; F7, the basis of F10 with 155°, 130°, 75°, 0°, 285°, 230°, and 205°; F9E, 9 fields with 40° equally spaced gantry angles; and FP, 7 posterior fields with 180°, 150°, 120°, 90°, 270°, 240°, and 210°. For each individual case of 10 patients, the customized constraints derived after optimization with the standard F10 technique were applied to 4 other field arrangements. The 4 new optimized plans of each individual case were normalized to achieve the same coverage of planning target volume (PTV){sub 63} {sub Gy} as that of the standard F10 technique. The F10 field arrangement exhibited the best coverage in PTV{sub 70} {sub Gy} and the least mean dose in the trachea-esophagus region. Furthermore, the F10 field arrangement demonstrated the highest level of conformity in the low-dose region and the least monitor unit. The F10 field arrangement performed more outstandingly than the other field arrangements in PTV{sub 70} {sub Gy} coverage and spared the central organ. This arrangement also exhibited the highest conformity and delivery efficiency. The F10 technique is recommended as the standard beam geometry for the SIB-IMRT of NPC.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2023

Modeling of Reactor Design and Optimization for Scale-Up of the Catalyxx Process for Ethanol Conversion to Higher Alcohol Biofuels

This report summarizes the results of a collaborative efforts between Oak Ridge National Laboratory (ORNL) and Catalyxx Inc. to investigate scale-up of Catalyxx’s Ethanol upgrading to higher alcohols process. The study was funded by the U.S. Department of Energy (DOE) Bioenergy Technologies Office (BETO) under CRADA (Cooperative Research and Development Agreement) No: NFE-20-08396. The project is part of the Direct Funding Opportunity (DFO) for Computational Science to Enable Bioenergy program which utilized computational toolsets developed by the Consortium for Computational Physics and Chemistry, a multi-laboratory consortium in BETO. The report here summarizes a packed-bed reactor modeling effort spanning the range from lab to industrial scale (from 4 gram to 5-ton catalyst beds), and examining reactor design, process optimization strategies, and suggested design and operating conditions for Catalyxx’s ethanol upgrading plants. The results in this report have been shared in monthly steering meetings and presentations are available in the shared data house owned by Catalyxx. The modeling effort helped to define optimum operation conditions for maximum alcohol selectivity and yield: i.e., temperature control scenarios ranging from adiabatic to isothermal, feed rate, pressure, and inlet H 2 /Ethanol ratio. The modeling results were verified at lab-(4 gram) and pre-pilot (4 kg) scales and has been used to evaluate a 5-ton packed-bed reactor and identify operating conditions to maximize the butanol yield. Special focus was given to understanding mass-transfer effects in the pre-pilot and pilot-scale reactors, over the domain of flow rate, pressure, feed composition, pellet size, shape, porosity, bed voidage, and reactor dimensions (i.e., length/diameter). Modeling was also used to evaluate innovative reactor design concepts such as water removal to improve alcohol selectivity and yield, and a reactor with an additional side inlet to facilitate quenching. These concepts were thoroughly explored, and potential benefits were disclosed. The results in this report are summarized and described qualitatively to protect the IP rights of Catalyxx. The details have been shared with the Catalyxx team in the regular steering meetings. At the end of the project, Catalyxx Inc. announced a successful demonstration of pilot scale operation in Seville, Spain.

02 PETROLEUM↗
DOE OSTI2026

Intrusive Uncertainty Quantification and Optimal Experiment Design in the Open-Source Pyomo Ecosystem

This contribution describes ParmEst and Pyomo.DoE, two pillars of the open-source Python-based Pyomo ecosystem for computational optimization with (partial differential) algebraic equation mathematical models. Specifically, ParmEst facilitates intrusive frequentist parameter estimation (PE) and uncertainty quantification (UQ) through built-in features, such as covariance matrix estimation, bootstrapping, and likelihood ratio tests. Complementary, Pyomo.DoE enables optimal experiment design by maximizing various metrics of the Fisher information matrix, such as A-optimality (trace), D-optimality (determinant), E-optimality (minimum eigenvalue), and ME-optimality (condition number). ParmEst and Pyomo.DoE can solve high-dimensional optimization problems by leveraging the model structure and exact derivative information. Finally, we will discuss future opportunities to integrate PE and UQ capabilities with optimization under uncertainty, including robust optimization with non-convex models via PyROS.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Technical Design and Optimization of a HLW-Repository in the Gorleben Salt Dome including Detailed Design of the Sealing System - 13305

The preliminary safety analysis for a HLW repository at Gorleben, the potential repository site in Germany, takes into account an updated set of data on the amounts and types of expected heat generating waste, the documented results of the exploration of the Gorleben salt dome, and the 'Safety Requirements Governing the Final Disposal of Heat-Generating Radioactive Waste' as at 30 September 2010. A repository design was developed for two emplacement concepts (drift disposal and borehole disposal) mainly influenced by the thermal impact of the heat-generating waste on the host rock and taking into account mining constrains. According to the objective to create the conditions for a safe containment of the waste containers in the host rock, a closure concept consisting of backfilling and sealing measures was developed. The repository was designed in such a way that retrievability requirements can be met for all waste containers within the operating phase of the repository. In addition, it could be shown that sufficient measures for ensuring subcriticality are provided both during the operational and the post-closure phases of the repository. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

Novel free-form hohlraum shape design and optimization for laser-driven inertial confinement fusion

The hohlraum shape attracts considerable attention because there is no successful ignition method for laser-driven inertial confinement fusion at the National Ignition Facility. The available hohlraums are typically designed with simple conic curves, including ellipses, parabolas, arcs, or Lame curves, which allow only a few design parameters for the shape optimization, making it difficult to improve the performance, e.g., the energy coupling efficiency or radiation drive symmetry. A novel free-form hohlraum design and optimization approach based on the non-uniform rational basis spline (NURBS) model is proposed. In the present study, (1) all kinds of hohlraum shapes can be uniformly represented using NURBS, which is greatly beneficial for obtaining the optimal available hohlraum shapes, and (2) such free-form uniform representation enables us to obtain an optimal shape over a large design domain for the hohlraum with a more uniform radiation and higher drive temperature of the fuel capsule. Finally, a hohlraum is optimized and evaluated with respect to the drive temperature and symmetry at the Shenguang III laser facility in China. The drive temperature and symmetry results indicate that such a free-form representation is advantageous over available hohlraum shapes because it can substantially expand the shape design domain so as to obtain an optimal hohlraum with high performance.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗