Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “designed experiment”

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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Applying Constrained Bayesian Optimization to the Design of Critical Experiments

Often when planning a criticality experiment, many design configurations are iteratively investigated with a Monte Carlo transport code. The goal is that the experiment will be optimal with respect to some variable, like the fraction of fissions occurring at a certain energy range, while simultaneously being critical. Unfortunately, the Monte Carlo transport simulations are expensive, which can ultimately limit the number of configurations that can be explored. In this work, we present how Gaussian processes (GPs) can be used as a reduced-order model in a constrained Bayesian optimization (CBO) algorithm to design a criticality experiment. The GPs replace the Monte Carlo transport simulations that explore the design space. The CBO algorithm efficiently identifies new points in the design space to run the Monte Carlo transport code while respecting the criticality constraint. It does so in a manner that both improves the accuracy of the GP and finds the approximate global optimum. We demonstrate the performance of CBO with the design of a Thermal Epithermal eXperiment (TEX) for the criticality safety validation of nuclear waste models of the Hanford Tank Farm.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Design of Experiments Involving Molybdenum in SNL SPRF/CX Facility

This report is part of the collaboration with the Nuclear Criticality Safety Program and constitutes the “CED-2 report” of the experiments proposed in the SPRF/CX facility of SANDIA National Laboratories to contribute to the validation of Molybdenum in thermal energy spectrum. It supplements the study carried out in the CED-1 report by providing a more precise design of the proposed experiments and presents a complete evaluation of the experimental uncertainties. In the CED-1 report, corresponding to the preliminary design of the experiments, IRSN identified several promising configurations that could be implemented in the SPRF/CX facility of SNL. They use metallic molybdenum either in the form of foils between the UO 2 pellets inside BUCCX rods, or in the form of sleeves surrounding 7uPCX rods. In this CED-2 report, a new design using molybdenum sleeves surrounding BUCCX rods is also analyzed and the experimental uncertainties of all the proposed configurations are estimated. Given the constraints to carry out the experiments and the costs associated with the manufacturing of the foils, the experiments using molybdenum foils are discarded. Similarly, the design using molybdenum sleeves around BUCCX rods leads to significant manufacturing costs which could certainly be partially offset by use of existing grids but which would lead to slightly lower values of the integral sensitivities to the cross sections of molybdenum. Consequently, the design using molybdenum sleeves around 7uPCX rods is favored insofar as it presents higher $k_{eff}$ sensitivities to the molybdenum cross sections and that there is still possibility to reduce the number of sleeves to reduce the cost of experiments. Regarding feedback on nuclear data in support of criticality safety assessment, one of the advantages of the work described here is that the proposed experiments are not correlated with the MIRTE and FP experiments using molybdenum. In addition, they lead to higher sensitivity values in the thermal energy range than the existing experiments and partly “cover” the first resonance of the 95 Mo, which is a real advantage for improving knowledge on molybdenum cross sections.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Accelerate Nuclear Research and Development by Reducing Time and Cost Spend in the Pre-conceptual Design Phase of Advanced Reactor Experiments

The design process of every new concept, such as advanced nuclear reactors or associated experiments, starts with the pre-conceptual design phase. In this phase, the viability of a wide range of design options needs to be assessed quickly, to understand the operating envelope and its feasibility. A variety of physics models (thermal-hydraulics, neutronics, mechanical design, etc.) has to be considered at this very first design stage and optimum component sizes and materials (e.g. heat exchangers, piping, turbomachinery, coolant type, etc.) have to be chosen for a given set of boundary conditions (e.g. heat source, heat sink, flow rate, etc.). Detailed solutions such as provided by high fidelity methods like computational fluid dynamics (CFD), Monte Carlo methods, etc. and even lower fidelity tools such as system or subchannel codes, etc. are usually not used during the pre-conceptual design due to the relatively long time needed to create input models, the computational time to obtain a solution and the lack of flexibility to quickly investigate different combinations of components, individual component sizes and material properties. High fidelity tools are usually only employed in the conceptual design and later phases once a base concept has been identified during the pre-conceptual design stage. The current practice during the pre-conceptual design stage is that analysts collect the needed equations, material properties, closure laws, etc. and create ad-hoc solutions form scratch for every new problem. There clearly is a lack of a flexible scoping tool that can be used during pre-conceptional design before higher fidelity tools (as described above) come into play. To reduce user errors in ad-hoc solutions and increase fidelity and efficiency, this project aims to investigate and develop a user-friendly scoping tool to address the thermal-hydraulic designing needs during preconceptual experiment design, i.e. Thermal-hydraulic Research Universal Scoping Tool (TRUST). The success of TRUST will provide the nuclear engineers with an easy-to-use and affordable calculator for early reactor system design and optimization.

42 ENGINEERING↗
DOE OSTI2024

Optimizing Batch Crystallization with Model-based Design of Experiments

Adaptive and self-optimizing intelligent systems such as digital twins are increasingly important in science and engineering. Digital twins utilize mathematical models to provide added precision to decision-making. However, physics-informed models are challenging to build, calibrate, and validate with existing data science methods. Model-based design of experiments (MBDoE) is a popular framework for optimizing data collection to maximize parameter precision in mathematical models and digital twins. In this work, we apply MBDoE, facilitated by the open-source package Pyomo.DoE, to train and validate mathematical models for batch crystallization. We quantitatively examined the estimability of the model parameters for experiments with different cooling rates. This analysis provides a quantitative explanation for the heuristic of using multiple experiments at different cooling rates.

Lynch, Hailey↗
DOE OSTI2025

Statistical Design of Experiments Enables Rapid Exploration of Perfluorobutane Sulfonate Degradation

The phase-out of long-chain PFAS has led to the proliferation of highly recalcitrant short-chain analogs, and mineralization technologies for these short-chain PFAS are needed to mitigate their deleterious effects on environmental and human health. In this study, we utilize a statistical design of experiments, specifically, response surface methodology, to rapidly evaluate the electrochemical degradation of the short-chain PFAS, perfluorobutane sulfonate (PFBS). We evaluate the impacts of the three primary electrochemical parameters (concentration of PFBS, concentration of supporting electrolyte, and applied current) over multiple orders of magnitude on the three primary reaction outcomes of electrochemical PFBS degradation (incomplete PFBS decomposition, complete PFBS mineralization as fluorine, and anodic energy consumption). Our results correspond with literature and clearly identify the well-known tradeoff between energy consumption and complete mineralization. Intriguingly, partial PFBS decomposition and energy consumption demonstrate nonlinear dependencies in the current/supporting electrolyte concentration space and the current/PFBS concentration space, respectively. These findings highlight the utility of the response surface methodology model to efficiently interrogate a large parameter space, identifying both common results and less-obvious interactions between electrochemical parameters and their influences on reaction outcomes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Model-Based Sequential Design of Experiments for Pilot Testing of Novel Water-Lean CO2 Capture Solvent

Poster for the 2024 Fossil Energy and Carbon Management Meeting. It summarizes work done on process modeling and uncertainty quantification in preparation for the test campaign at the National Carbon Capture Center for a general audience. The poster includes sections detailing background on the EEMPA solvent, sequential design of experiments, process modeling (including results from the model), uncertainty quantification, and the goals of the test campaign.

Hedrick, Katherine↗
DOE OSTI2024

Modeling, Optimization, and Design of Experiments of a Rotary Packed Bed Contactor for NGCC–Based CO2 Capture Using Solid Sorbents

This presentation will be given at the 2024 AICHE annual meeting on October 30th. This presentation focuses on modeling a rotary packed bed contactor for CO2 capture. The RPB is an alternative contactor to fixed beds and optimization is performed to minimize the energy requirement. A design of experiments case study of the RPB is also performed.

Hughes, Ryan↗
DOE OSTI2023

Sustainable bioleaching of lithium-ion batteries for critical metal recovery: Process optimization through design of experiments and thermodynamic modeling

Recycling spent lithium-ion batteries (LIBs) could alleviate supply risks for critical metals and be less harmful to the environment compared to new production of metals from mining. Developing a cost-effective LIB bioleaching process could be a promising alternative to traditional energy-intensive recycling technologies. Here, this study aimed to optimize bioleaching conditions for maximum economic competitiveness through design of experiments using iterative response surface methodology (RSM), assisted by thermodynamic modeling. The optimal condition was identified as 2.5% pulp density in 75 mM gluconic acid biolixiviant at 55°C for 30 h which could recover 57%–84% of nickel, 71%–86% of cobalt, and 100% of lithium and manganese, yielding a 17%–26% net profit margin. The recommended pulp density and acid concentrations, together with the observed metal solubilization, were supported by thermodynamic modeling predictions. Our study demonstrated that combining RSM with thermodynamic simulations could be a powerful tool for optimizing bioleaching conditions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Integral Experiment Request 523 Feasibility Study (Summary Report)

This report documents the feasibility phase of the Critical Experiment Design (CED) conducted as part of integral experiment request (IER) 523. The purpose of IER-523 is to explore the effects of using 35 weight percent enriched uranium dioxide-beryllium oxide (UO 2 -BeO) material on critical configurations using the Seven Percent Critical Experiment (7uPCX) at Sandia National Laboratories (Sandia). Preliminary experiment design concepts, neutronic analysis results, and proposed paths for continuing the CED process are presented.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Understanding and improving anode performance in an alkaline membrane electrolyzer using statistical design of experiments

The behavior of the oxygen-evolving positive electrode (i.e. anode) in the anion exchange membrane water electrolyzer (AEMEL) is complex and influenced by several factors. Very few studies have been performed to understand oxygen evolution reaction (OER) behavior by optimizing the individual factors that influence performance. Here, this study highlights the effects of catalyst loading, catalyst selection, porous transport layer (PTL) type and conductive additive content. The influence of each factor is elucidated through a design of experiments (DoE) approach with a full statistical analysis. Electrochemical data, alongside Pareto charts, parametric trends and their mutual interactions are discussed. This DoE approach is also helpful in making useful predictions and discovering new combinations to be tested. The end result was a high-performance AEMEL able to operate at a current density of 1.0 A/cm 2 at 1.80 V with IrOx OER and PtNi hydrogen evolution reaction (HER) catalysts using 0.3 M KOH fed to the anode. Even lower operating voltage was observed with PbRuOx catalyst at the anode, 1.64 V @ 1.0 A/cm 2 , though the cell decay rate was higher. Lastly, a IrOx/PtNi cell was stably operated continuously for 30 days (720 h) at 1.0 A/cm 2 . This study can serve as a guide for optimal electrode design with insights into component-performance compromises, which can aid in making design choices and performing techno-economic analyses.

08 HYDROGEN↗
DOE OSTI2023

Design optimization of an ethanol heavy-duty engine using design of experiments and bayesian optimization

Diesel-fueled engines still hold a large market share in the medium and heavy-duty transportation sector. However, the increase in fossil fuel prices and the strict emission regulations are leading engine manufacturers to seek cleaner alternatives without a compromise in performance. Alcohol-based fuels, such as ethanol, offer a promising alternative to diesel fuel in meeting regulatory demands. Ethanol provides cleaner combustion and lower levels of soot due to its chemical properties, in particular its lower level of carbon content. In addition, the stoichiometric operating conditions of alcohol fueled engines enable the mitigation of NOx emissions in aftertreatment stage. With the promise of retrofitting diesel engines to run on ethanol to reduce emissions, the thermal efficiency of these engines remains the primary optimization target. In order to find the optimal ethanol-fueled engine design that maximizes the thermal efficiency, a large design space needs to be investigated using engineering tools. In this study, previous research by the authors on optimizing the design of a single-cylinder ethanol-fueled engine was extended to explore the design space for a heavy-duty multi-cylinder engine configuration. A heavy-duty engine setup with multiple operating conditions at different engine speeds and loads were considered. A design optimization analysis was performed to identify the potential designs that maximize the indicated thermal efficiency in an ethanol-fueled compression ignition engine. First, a computational fluid dynamics (CFD) model of the engine was validated using experimental data for four drive cycle points. Using a design of experiments (DoE) approach and a parameterized piston bowl geometry, the model was then exercised to explore the relationship among geometric features of the piston bowl and spray targeting angle and indicated thermal efficiency across all tested operating conditions. After evaluating 165~candidate designs, a piston bowl geometry was identified that yielded an increase between 1.3 to 2.2 percentage points in indicated thermal efficiency for all tested conditions, while satisfying the operational design constraints for peak pressure and maximum pressure rise rate. The increased performance was attributed to enhanced mixing that led to the formation of a more homogeneous distribution of in-cylinder temperature and equivalence ratio, higher combustion temperatures, and shorter combustion duration. Finally, a Bayesian optimization (BOpt) analysis was employed to find the optimal piston bowl geometry with a fixed spray injector angle for one of the operating conditions. Using BOpt, a piston candidate was identified that resulted in a 1.9~percentage point increase in thermal efficiency from the baseline design, yet only required 65\% of the design samples investigated using the DoE approach.

Tekgul, Bulut↗
DOE OSTI2024

Sequential Design of Experiments for Pilot Testing of Novel Solvent System

The CCSI2 program is supporting a six-month test campaign at the National Carbon Capture Center (NCCC) for evaluation of a novel water-lean solvent. This presentation describes CCSI2’s efforts in process modeling of the solvent system for both coal and natural gas-based flue gas sources and initial uncertainty quantification (UQ) work to estimate parametric uncertainty in key sub-models of interest (e.g., thermodynamics, mass transfer, reaction kinetics). Moreover, perspective is provided on how UQ and sequential design of experiments (SDoE) tools are used to assess the impact of model uncertainty on projected process performance, use this information to optimize data collection during the campaign, and refine process models through data collection. This framework is expected to reduce the overall model uncertainty, and thus risk associated with scale-up as the process moves towards commercialization.

Morgan, Joshua↗
DOE OSTI2025

Design of Experiments for Dynamic Test Runs in Solvent-Based CO 2 Capture Pilot Plants

Test runs in the pilot plants consume significant resources, and therefore, the learning from test runs should be maximized. Test runs conducted in the pilot plants are often steady state. It takes several hours for reaching steady-state in the pilot plants, and thus, the duration of the test runs needs to be long even for collecting few steady-state data points. On the other hand, a large number of measurements can be collected through dynamic test runs in a short span of time. This paper presents a systematic design of dynamic experiments (DoDEs) for identifiability of model parameters, which is achieved by persistently exciting the inputs signals. A pseudorandom binary sequence (PRBS) is designed as the input signal for DoDE due to its efficiency in obtaining sufficient spectral content. However, due to the long sequence size of the PRBS signal, a Schroeder-phase input signal, which is a multisine signal, is also designed. Tests for both types of signals are run in the Pilot Solvent Test Unit (PSTU) at the National Carbon Capture Center in Wilsonville, Alabama. The transient data are used to solve dynamic data reconciliation and parameter estimation problem. The estimated parameters are found to be not only superior to those estimated from using data collected from hundreds of steady-state test runs in a nonreactive (air–water) system, but the parameters could be estimated by using the dynamic data collected for about 24 h from the pilot plant for the MEA-H 2 O–CO 2 system.

CO2 capture↗
DOE OSTI2025

Sample glue layer investigation and mitigation for laser induced prompt impulse experiments

Understanding longer timescale material reactions under dynamic stress loading is critical for applications in materials engineering, shock physics, and planetary science. Prompt impulse experiments generate lower pressures since the ablator—the material first removed by the laser—is thicker and farther from the diagnostic plane, capturing aggregate material responses from the initial shock wave, rarefaction waves, and later time effects. This complexity demands thorough material characterization and simulation support. Since traditional sample construction is specific to supported shock experiments, designing prompt impulse experiments requires reconsideration around target design and sample engineering. Here, we present sample preparation techniques, experimental investigations, and theoretical simulations to investigate glue layer impacts, aiming to standardize samples for consistent data at lower laser fluences. We find that glue layers <30 μm have a minimal impact on peak velocity and pulse shape. The peak velocity scales linearly with glue layer thickness until a glue layer of 75 μm. For glue layers >75 μm, the peak velocity no longer scales with thickness; however, the pulse shape continues to degrade as described by simulations.

Lasers↗
DOE OSTI2022

Stochastic Learning Approach for Binary Optimization: Application to Bayesian Optimal Design of Experiments

Here, we present a novel stochastic approach to binary optimization suited for optimal experimental design (OED) for Bayesian inverse problems governed by mathematical models such as partial differential equations. The OED utility function, namely, the regularized optimality criterion, is cast into a stochastic objective function in the form of an expectation over a multivariate Bernoulli distribution. The probabilistic objective is then solved by using a stochastic optimization routine to find an optimal observational policy. This formulation (a) is generally applicable to binary optimization problems with soft constraints and is ideal for OED and sensor placement problems; (b) does not require differentiability of the original objective function (e.g., a utility function in OED applications) with respect to the design variable, and thus it enables direct employment of sparsity-enforcing penalty functions such as $\ell_0$, without needing to utilize a continuation procedure or apply a rounding technique; (c) exhibits much lower computational cost than traditional gradient-based relaxation approaches; and (d) can be applied to both linear and nonlinear OED problems with proper choice of the utility function. The proposed approach is analyzed from an optimization perspective with detailed convergence analysis of the optimization approach and is also analyzed from a machine learning perspective with correspondence to policy gradient reinforcement learning. The approach is demonstrated numerically by using an idealized two-dimensional Bayesian linear inverse problem and validated by extensive numerical experiments carried out for sensor placement in a parameter identification setup.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Design of Critical Experiments Involving Graphite elements at the IPEN/MB-01 Plate-Type Core

A series of critical experiments were designed involving the use of characterized graphite elements in the new plate-type core of the IPEN/MB-01 reactor. Eleven configurations with different graphite quantities are considered, each producing distinct effects on neutron fluxes and offering opportunities to analyze varying sensitivities to k eff in the system. The analysis shows that the experiments can be performed with acceptably low k eff uncertainties considering an adequate characterization of the graphite elements to be used. The sensitivity results obtained using SCALE TSUNAMI calculations show that the experiments have a notable k eff sensitivity coefficient to graphite. In the configurations tested, the k eff sensitivity to graphite TSL is low. This experiment will be useful for criticality safety validation of applications using uranium fuel enriched to around 19.75 wt % 235 U, light water and graphite. It will also be useful to gain more insight into graphite material properties and their effect on k eff as a result of using the well-characterized graphite elements. The execution of the experiments is planned for the summer of 2025. The 11 designed configurations serve as a basis for the final design, and fewer configurations will be executed. Once executed, these critical experiments will be evaluated and submitted for publication in the International Criticality Safety Benchmark Evaluation Project Handbook, supporting the DOE/NRC Collaboration for Criticality Safety Support for Commercial-Scale HALEU for Fuel Cycles and Transportation project goal.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Integral Experiment Request 554: CED-2 Summary Report

This report summarizes the critical experiment design 2 (CED-2) or final design study for Integral Experiment Request 554 (IER-554). This experiment describes the effects and importance of adding a commercially available neutron absorber material to a known light-water low-enriched uranium assembly. The assembly in question is the Seven Percent Critical Experiments (7uPCX) at Sandia National Laboratories. The neutron absorber plates considered for the experiment are known as Boralcan and are made of boron carbide (B 4 C) particles embedded in 1100 aluminum alloy. The concentrations of B 4 C and 1100 aluminum were changed as well as the thickness and the positions of the plates, and the fuel rod configuration was adapted to ensure that the assembly would be critical in each case studied. A total of 6 critical configurations, each with a neutron absorber plate inserted, are described in this report. No results of high-quality integral experiments involving neutron absorbers made with B 4 C and 1100 aluminum plates are currently publicly available. Sensitivity to the neutron absorber plate material definition, isotopes, and cross sections of specific regions and configurations are also analyzed. As part of the final design of the experiment, a safe plate holder made of 3003 aluminum was designed. The study results indicate that these experiments are achievable with sufficiently low uncertainties and minimal modification to the assembly, and the CED-3 phase can start when funding allows.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗