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At least 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
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 OSTI2016

The IAEA coordinated research project on modular HTGR safety design: status and outlook - 18608

The IAEA Coordinated Research Project (CRP) on Modular High Temperature Gas-cooled Reactor (HTGR) Safety Design started in December 2014 and is now in its second year of implementation. The project investigates and makes proposals on safety design criteria by not only considering the existing water cooled reactors safety requirements for nuclear power plant design but also making use of past and current experience of HTGR licensing in the IAEA member states. Two approaches are being followed to establish the criteria. The first is to develop and apply a safety design process to specific reactor de-signs. The second is to use the existing IAEA specific safety requirements for designs based on water cooled reactor technology and then through expert judgment and review propose changes that is needed to make it applicable to HTGRs. The detailed project content and a description of modular HTGRs and its safety features are given. This informs the comments made on the applicability of the existing requirements and the examples of newly pro-posed HTGR specific safety requirements under development. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2016

Multifunctional 2D- Materials: Selenides and Halides

Material is the key component and controls the performance of the detectors, devices and sensors. The materials design, processing, growth and fabrication of bulk and nanocrystals and fabrication into devices and sensors involve multidisciplinary team of experts. This places a large burden on the cost of the novel materials development. Due to this reason there is a big thrust for the prediction of multifunctionality of materials before design and development. Up to some extent design can achieve certain properties. In multinary materials processing is also a big factor. In this presentation, examples of two classes of industrially important materials will be described.

Singh, N. B.↗
DOE OSTI2024

TEAMER Technical Support for Aquantis (Modeling): Cooperative Research and Development Final Report, CRADA Number CRD-21-17763

NREL will provide numerical modelling support to Requestor by completing four successive stages of numerical modeling effort which are capable of accurate predicting the performance of the Aquantis turbine. NREL will develop a baseline OpenFAST model (a couple model of AeroDyn and ElastoDyn solver) of the Aquantis turbine, subsequently couples this model to OrcaFlex or within OpenFAST framework to preliminarily design and explore a full floating tidal turbine system in a control co-design process.

16 TIDAL AND WAVE POWER↗
NASA NTRS2010

Similarity Rules for Scaling Solar Sail Systems

Future science missions will require solar sails on the order of 200 square meters (or larger). However, ground demonstrations and flight demonstrations must be conducted at significantly smaller sizes, due to limitations of ground-based facilities and cost and availability of flight opportunities. For this reason, the ability to understand the process of scalability, as it applies to solar sail system models and test data, is crucial to the advancement of this technology. This paper will approach the problem of scaling in solar sail models by developing a set of scaling laws or similarity criteria that will provide constraints in the sail design process. These scaling laws establish functional relationships between design parameters of a prototype and model sail that are created at different geometric sizes. This work is applied to a specific solar sail configuration and results in three (four) similarity criteria for static (dynamic) sail models. Further, it is demonstrated that even in the context of unique sail material requirements and gravitational load of earth-bound experiments, it is possible to develop appropriate scaled sail experiments. In the longer term, these scaling laws can be used in the design of scaled experimental tests for solar sails and in analyzing the results from such tests.

Canfield, Stephen L.↗
DOE OSTI2018

A Unified Modeling Framework to Advance Biofuel Production from Microalgae

Modeling efforts to understand the financial implications of microalgal biofuels often assume a static basis for microalgae biomass composition and cost, which has constrained cultivation and downstream conversion process design and limited in-depth understanding of their interdependencies. For this work, a dynamic biological cultivation model was integrated with thermo-chemical/biological unit process models for downstream biorefineries to increase modeling fidelity, to provide mechanistic links among unit operations, and to quantify minimum product selling prices of biofuels via techno-economic analysis. Variability in design, cultivation, and conversion parameters were characterized through Monte Carlo simulation, and sensitivity analyses were conducted to identify key cost and fuel yield drivers. Cultivating biomass to achieve the minimum biomass selling price or to achieve maximum lipid content were shown to lead to suboptimal fuel production costs. Depending on biomass composition, both hydrothermal liquefaction and a biochemical fractionation process (combined algal processing) were shown to have advantageous minimum product selling prices, which supports continued investment in multiple conversion pathways. Ultimately, this work demonstrates a clear need to leverage integrated modeling platforms to advance microalgae biofuel systems as a whole, and specific recommendations are made for the prioritization of research and development pathways to achieve economical biofuel production from microalgae.

09 BIOMASS FUELS↗
DOE OSTI2025

Genetic algorithm optimization of nuclear criticality experiment for reduction of intermediate-energy 239 Pu nuclear data uncertainties

Nuclear criticality experiments are conducted to investigate specific nuclear data important for safe handling and storage of fissile materials, reactor design and operation, and the validation of radiation transport codes. Incorrect or uncertain nuclear data can prohibitively impact operational safety limits, reactor licensing, and predictive simulation capability; therefore, integral measurements from criticality experiments are necessary and should be performed frequently. To maximize the impact of the integral measurements, it is important to consider experiment geometry, material selection, and component dimensions. When taking these considerations into account, the experiment design process becomes iterative and very time intensive. This work utilizes a genetic algorithm to efficiently explore potential nuclear criticality experiment designs for the Laboratory Directed Research & Development project PARADIGM (PARallel Approach of Differential and InteGral Measurements) at Los Alamos National Laboratory. In this paper, the building blocks of the genetic algorithm are discussed in detail, the genetic algorithm methodology is verified, and the genetic algorithm is used to produce three candidate experiment models for the final PARADIGM design. The three candidate models produced by the genetic algorithm consist of copper-reflected assemblies containing 14 repeating units of alumina, graphite, boron, and plutonium plates. Furthermore, in addition to the optimization results, final design considerations are also discussed for designs with a height and/or weight very close to or slightly above assembly machine operational limits.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Building Efficiency Technologies by Tomorrow’s Engineers and Researchers (BETTER) Capstone. Final Technical Report

BETTER Capstone supported 29 student project teams consisting of 155 students over two years in developing transformative building energy efficiency technologies through a capstone design experience. Capstone is the culmination of an undergraduate student’s engineering education. Interdisciplinary teams of students spent a semester designing and prototyping a technological solution for a variety building energy efficiency problems. During this experience students utilized the full design process, including the manufacturing and testing of a prototype solution, as well as publically demonstrating the solution at the Capstone Design Expo. As part of this project, students explored modern manufacturing techniques and gained hands-on experience with these techniques to produce their prototype technologies. This research added to the understanding of the challenges within building technology education and engagement with industry. One goal of the project was to help break the chicken-and-egg problem with getting students to engage more deeply with the building technology industry. It was learned however that this industry is less interested in trying innovative new concept but rather interested in hiring graduates for existing conventional building efforts. While none of the projects yielded commercial success, much individual student growth and learning was accomplished, which is a long-term benefit to the public at large.

42 ENGINEERING↗
DOE OSTI2023

Downselection and Basic Properties of Additively Manufactured ODS Alloys

In the AMMT program the work package for development of new materials aimed to explore the advanced manufacturing techniques that are feasible for the manufacturing of advanced materials components. A merit-based feasibility study was attempted to identify an accelerated development path for dispersion strengthened (ODS) alloys by creatively combining additive manufacturing (AM) technologies with the recent advances in ODS materials and traditional manufacturing technologies. For the fiscal year, the primary tasks were focused to develop additive manufacturing (AM) and post-build processing route for oxide dispersion strengthened (ODS) ferritic (Fe-Cr alloy or 14YWT) and austenitic (Fe-Cr-Ni alloys or 316L and 316H) alloys and to perform basic microstructural and mechanical characterizations to provide feedbacks to the alloy and processing design. Further, the multi-laboratory effort created collaboratively a decision criteria matrix to evaluate and downselect the new materials processed by advanced manufacturing methods. This report is to describe the ODS alloy processing routes combining AM processes and post-build thermomechanical treatments, mechanical and microstructural characteristics of the newly developed materials, and the application results of the decision criteria matrix for the AM ODS alloys including a downselected material and feasible processing route. Key mechanical test results including tensile strength, tensile ductility, and fracture toughness data and are reported and explained. Higher strength was measured from the ferritic ODS alloys, while higher ductility and fracture toughness were measured from the austenitic ODS alloys. Many of the decision criteria were scored the same for the AM ferritic and austenitic ODS alloys, however, the generally known fact that the austenitic alloys have higher corrosion resistance and significantly better ductility. Although these scores are not significantly different to make them highly discernable, the austenitic ODS alloys were downselected to be the primary materials group in the future research on ODS materials in AMMT program.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Machine Learning for Automated Weld Quality Monitoring and Control

Resistance Spot Welding (RSW) is a critical process in the automotive industry, valued for its cost-effectiveness, short cycle time, and robustness. However, achieving consistent high-quality joints remains challenging due to the complex interplay of various factors, like materials, processes, and manufacturing uncertainties, etc. Under the collaborative project between Oak Ridge National Laboratory (ORNL) and General Motors (GM), we have developed a robust and expansible machine learning (ML) framework aimed at enhancing quality control in RSW. By harnessing the power of machine learning, we have developed the ability to ensure every aspect of the welding process, from the initial process design stage to the final weld joint quality. The framework operates by analyzing a variety of data streams, including in-line process signals, process parameters, materials, and postprocessed weld joint data. Through this analysis, the models have been trained to detect deviations from optimal quality standards, leveraging their ability to identify signature data patterns and anomalies within in-line signals and construct complex correlations between these signals and weld quality parameters. Meanwhile, the machine learning framework is designed to adapt to a variety of materials, including high strength steels and aluminum alloys, etc. Its flexible architecture facilitates the incorporation of diverse data sources and features, enabling precise modeling and prediction across a broad range of material properties and weld quality variables. The expansible ML frameworks represent a promising transformation in weld quality monitoring and control, empowering industry to achieve high levels of efficiency, consistency, and reliability in manufacturing.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Machine Learning for Automated Weld Quality Monitoring and Control

Resistance Spot Welding (RSW) is a critical process in the automotive industry, valued for its cost-effectiveness, short cycle time, and robustness. However, achieving consistent high-quality joints remains challenging due to the complex interplay of various factors, like materials, processes, and manufacturing uncertainties, etc. Under the collaborative project between Oak Ridge National Laboratory (ORNL) and General Motors (GM), we have developed a robust and expansible machine learning (ML) framework aimed at enhancing quality control in RSW. By harnessing the power of machine learning, we have developed the ability to ensure every aspect of the welding process, from the initial process design stage to the final weld joint quality. The framework operates by analyzing a variety of data streams, including in-line process signals, process parameters, materials, and postprocessed weld joint data. Through this analysis, the models have been trained to detect deviations from optimal quality standards, leveraging their ability to identify signature data patterns and anomalies within in-line signals and construct complex correlations between these signals and weld quality parameters. Meanwhile, the machine learning framework is designed to adapt to a variety of materials, including high strength steels and aluminum alloys, etc. Its flexible architecture facilitates the incorporation of diverse data sources and features, enabling precise modeling and prediction across a broad range of material properties and weld quality variables. The expansible ML frameworks represent a promising transformation in weld quality monitoring and control, empowering industry to achieve high levels of efficiency, consistency, and reliability in manufacturing.

42 ENGINEERING↗
DOE OSTI2026

Making Small-Volume Heat Pump Water Heaters Larger: A Design Framework for Integrated Phase Change Material Heat Exchangers

Those that use electricity for water heating, the majority use resistive elements rather than heat pump water heaters (HPWHs), the latter of which use 60-70% less energy than the former. One major barrier to wider HPWH adoption is the added equipment required, which prevents current 50-80-gallon tanks on the market from fitting into smaller utility closets sized for 30-40 gallons, such as those found in manufactured housing. Additionally, these smaller HPWHs tend to underperform relative to their larger counterparts. One solution that addresses both space and performance concerns is thermal energy storage, and in particular, phase change materials (PCMs). PCMs have been studied extensively in building envelope and HVAC systems, but remain a nascent technology in residential water heating. While water itself has a uniquely high energy storage capacity, PCMs have an even higher energy storage density, thus providing the potential to elevate the performance of 40-gallon HPWHs to that of 50-gallon or larger tanks. This research is part of a larger project that seeks to utilize thermal energy storage to enable decarbonized water heating in low-income communities. In this study, we outline the design process used to produce novel PCM heat exchangers for use in small-volume HPWH tanks, including the identification of design constraints and performance targets relevant to real-world applications. In order to ensure optimal PCM utilization and tank storage capacity, we focus here on co-maximizing surface area and PCM volume in the heat exchangers; therefore, this research targets triply periodic minimal surface (TPMS) lattices. TPMS lattices boast enhanced heat transfer capabilities compared to traditional heat exchanger geometries and offer highly tailorable designs; thus, they pair well with the growing field of additive manufacturing, or 3D printing. Starting with a suite of TPMS lattices, we demonstrate a systematic approach for narrowing down feasible designs that comply with identified constraints while meeting PCM performance objectives.

25 ENERGY STORAGE↗
DOE OSTI2026

Design Considerations for Phase Change Material-Incorporated Heat Exchangers in Water Heating

In recent years, the buildings sector has seen major pushes towards decarbonization through innovations that promote deep electrification. 20% of an average household's energy use comes from water heating, and in the US, over half of all households still use gas water heaters. Of those that use electricity for water heating, the majority use resistive elements rather than heat pump water heaters (HPWHs), the latter of which use 60-70% less energy than the former. However, HPWHs tend to have larger dimensions, preventing current 50-80-gallon tanks on the market from fitting into smaller utility closets sized for 30-40 gallons, such as those found in manufactured housing. Additionally, these smaller HPWHs tend to underperform relative to their larger counterparts. One solution that addresses both space and performance concerns is thermal energy storage, and in particular, phase change materials (PCMs). This study outlines the design process used to produce novel PCM heat exchangers for use in small-volume HPWH tanks, including the identification of design constraints and performance targets relevant to real-world applications. To ensure optimal PCM utilization and tank storage capacity, this works seeks to co-maximize surface area and PCM volume; therefore, this research targets triply periodic minimal surface (TPMS) lattices, which boast enhanced heat transfer capabilities compared to traditional heat exchanger geometries. Starting with a suite of TPMS lattices, we demonstrate a systematic approach for narrowing down feasible designs that comply with identified constraints while meeting PCM performance objectives. Our current results indicate that tuning lattice properties can effectively produce geometries that provide enough energy storage to achieve a 50-gallon capacity out of a 40-gallon HPWH, even when placing the PCM heat exchanger inside the tank. Additionally, we demonstrate successful fabrication of lattices with these tuned properties.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1973

Automated procedure for design of wing structures to satisfy strength and flutter requirements

A pilot computer program was developed for the design of minimum mass wing structures under flutter, strength, and minimum gage constraints. The wing structure is idealized by finite elements, and second-order piston theory aerodynamics is used in the flutter calculation. Mathematical programing methods are used for the optimization. Computation times during the design process are reduced by three techniques. First, iterative analysis methods used to reduce significantly reanalysis times. Second, the number of design variables is kept small by not using a one-to-one correspondence between finite elements and design variables. Third, a technique for using approximate second derivatives with Newton's method for the optimization is incorporated. The program output is compared witH previous published results. It is found that some flutter characteristics, such as the flutter speed, can display discontinous dependence on the design variables (which are the thicknesses of the structural elements). It is concluded that it is undesirable to use such quantities in the formulation of the flutter constraint.

Haftka, R. T.↗
NASA NTRS1984

A review of the silicon material task

The Silicon Material Task of the Flat-Plate Solar Array Project was assigned the objective of developing the technology for low-cost processes for producing polysilicon suitable for terrestrial solar-cell applications. The Task program comprised sections for process developments for semiconductor-grade and solar-cell-grade products. To provide information for deciding upon process designs, extensive investigations of the effects of impurities on material properties and the performance of cells were conducted. The silane process of the Union Carbide Corporation was carried through several stages of technical and engineering development; a pilot plant was the culmination of this effort. The work to establish silane fluidized-bed technology for a low-cost process is continuing. The advantages of the use of dichlorosilane is a siemens-type were shown by Hemlock Semiconductor Corporation. The development of other processes is described.

Lutwack, R.↗
NASA NTRS1986

Development of the Spartan 101 navigation and pointing timeline

This paper presents the techniques and analyses that were used to construct the Spartan 101 mission pointing timeline for the Space Shuttle Orbiter-detached portion of its flight. This covers the design process that had to transform requirements and constraints originating from the experimenter, the Space Transportation System, and the payload hardware design into a workable set of pointing instructions sequenced to mission events. The paper will discuss the technical approach used for initial attitude acquisition, determining target visibility, observation scheduling, and calculation of vehicle maneuvers.

Lambros, S. D.↗
NASA NTRS1990

A line-of-sight performance criterion for controller design of a proposed laboratory model

A line-of-sight performance criterion is derived for a proposed Controls Structures Interaction model, and its many uses in the control design process for fine pointing control are illustrated. A linearized line-of-sight (LOS) criterion is used for direct controller design and as a performance measure to judge different control methodologies. Numerical simulation results are shown where the three approaches: linear quadratic Gaussian theory, robust eigensystem assignment, and local velocity feedback are used for vibration control. Results indicate that the linear quadratic Gaussian controller, which incorporates a linearized LOS weighting matrix directly, yields good performance without wasting energy to control motions that have no influence on the LOS.

Lim, Kyong B.↗
NASA NTRS1990

Active control test on the Mini-Mast

A Linear Quadratic Gaussian (LQG) design process is presented and applied to a large flexible ground test facility, the Mini-Mast, for validation. For the design, nine displacement sensors were used. Three torque wheel actuators were used for damping augmentation. Results were dramatic, indicating an improvement in damping from 3 percent to 30 percent of critical. The tests proved the effectiveness of the procedure in designing effective vibration damping systems.

Montgomery, Raymond C.↗