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All sources NASA NTRS DOE OSTI

DOE OSTI2023

Co-design optimization of combined heat and power-based microgrids

With the emergent need for clean and reliable energy resources, hybrid energy systems, such as the microgrid, are widely adopted in the United States. A microgrid can consist of various distributed energy resources, for instance, combined heat and power (CHP) systems. Here, the CHP module is a distributed cogeneration technology that produces electricity and recaptures heat generated as a by-product. It is an energy-efficient technology converting heat that would otherwise be wasted to valuable thermal energy. For an optimal system configuration, this study develops a novel co-design optimization framework for CHP-based cogeneration microgrids. The framework provides the stakeholder with a method to optimize investments and attain resilient operations. The proposed co-design framework has a mixed integer programming (MIP) model that outputs decisions for both plant designs and operating controls. The microgrid considered in this study contains six components: the CHP, boiler, heat recovery unit, thermal storage system, power storage system, and photovoltaic plant. After solving the MIP model, the optimal design parameters of each component can be found to minimize the total installation cost of all components in the microgrid. Furthermore, the online costs from energy production, operation, maintenance, machine startup, and disruption-induced unsatisfied loads are minimized by solving the optimal control decisions for operations. Case studies based on designing a CHP-based microgrid with empirical data are conducted. Moreover, we consider both nominal and disruptive operational scenarios to validate the performance of the proposed co-design framework in terms of a cost-effective, resilient system.

42 ENGINEERING↗

NASA NTRS1994

Design and aerodynamic performance evaluation of a high-work mixed flow turbine stage

As axial and radial turbine designs have been pushed to their aerothermodynamic and mechanical limits, the mixed-flow turbine (MFT) concept has been projected to offer performance and durability improvements, especially when ceramic materials are considered. The objective of this NASA/U.S. Army sponsored mixed-flow turbine (AMFT) program was to determine the level of performance attainable with MFT technology within the mechanical constraints of 1997 projected ceramic material properties. The MFT geometry is similar to a radial turbine, exhibiting a large radius change from inlet to exit, but differing in that the inlet flowpath is not purely radial, nor axial, but mixed; it is the inlet geometry that gives rise to the name 'mixed-flow'. The 'mixed' orientation of the turbine inlet offers several advantages over radial designs by allowing a nonzero inlet blade angle yet maintaining radial-element blades. The oblique inlet not only improves the particle-impact survivability of the design, but improves the aerodynamic performance by reducing the incidence at the blade inlet. The difficulty, however, of using mixed-flow geometry lies in the scarcity of detailed data and documented design experience. This paper reports the design of a MFT stage designed with the intent to maximize aerodynamic performance by optimizing design parameters such as stage reaction, rotor incidence, flowpath shape, blade shape, vane geometry, and airfoil counts using 2-D, 3-D inviscid, and 3-D viscous computational fluid dynamics code. The aerodynamic optimization was accomplished while maintaining mechanical integrity with respect to vibration and stress levels in the rotor. A full-scale cold-flow rig test was performed with metallic hardware fabricated to the specifications of the hot ceramic geometry to evaluate the stage performance.

Neri, Remo N.↗

DOE OSTI2025

Large eddy simulation of wind farm performance in horizontally and vertically staggered layouts

This numerical investigation employs Large Eddy Simulation (LES) coupled with Actuator Disk Model (ADM) to evaluate wind farm layout optimization strategies. The study presents a systematic analysis of aligned, horizontal staggering, vertical staggering, and mixed (combination of horizontal and vertical) staggering configurations, aiming to establish optimal design parameters for enhanced power production. The investigation examines key performance metrics including mean velocity distributions, turbulence intensity characteristics, and power generation efficiency. Results demonstrate better performance of both horizontal and vertical staggering patterns compared to conventional aligned configurations, with horizontal staggering exhibiting notably higher power output than vertical arrangements. Our findings also suggest that mixed configurations, incorporating both horizontal and vertical staggering, can offer optimal performance characteristics. As a result, this research advances the understanding of wake interactions in complex wind farm layouts and provides design guidelines for maximizing wind farm power generation efficiency through strategic turbine positioning.

17 WIND ENERGY↗

DOE OSTI2024

Steam Generator Model Design Parameter Sensitivity Study Using Advanced Optimization Tools

This study focuses on design parameter sensitivity studies pertaining to a steam generator (SG) model, using both Python and machine-learning tools. The SG model is a mathematical representation (including fluid flow and heat transfer equations/models/correlations) of a steam-generating unit in a pressurized water reactor (PWR)-type small modular reactor (SMR) system. Design studies involve changing the model’s input design parameters (e.g., temperature, pressure, mass flow rate) to observe the resulting effects on the output of the system (e.g., heat transfer coefficient [HTC], Nusselt number, heat transfer performance). Sensitivity studies analyze the degree to which system output and/or desired parameters (e.g., HTC or heat transfer performance) are sensitive to changes in input parameters. By using machine-learning tools such as the Risk Analysis Virtual Environment (RAVEN) developed at Idaho National Laboratory (INL), detailed design parametric sensitivity studies and model optimization were performed. Six input parameters—namely, the pressure, temperature, and mass flow rate for the inlet of the primary-side (hot fluid) and secondary-side (cold fluid) of the SG—were randomly perturbed via RAVEN’s Monte Carlo Sampler module, using uniform distributions (±1% relative changes). The analysis results give valuable insights into SG system performance and optimization, and provide justification for researching optimized sensor placement to effectively monitor and obtain experimental data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2024

Steam Generator Model Design Parameter Sensitivity Study Using Advanced Optimization Tools

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS1983

Parametric study of critical constraints for a canard configured medium range transport using conceptual design optimization

Constrained parameter optimization was used to perform optimal conceptual design of both canard and conventional configurations of a medium range transport. A number of design constants and design constraints were systematically varied to compare the sensitivities of canard and conventional configurations to a variety of technology assumptions. Main landing gear location and horizontal stabilizer high-lift performance were identified as critical design parameters for a statically stable, subsonic canard transport.

Arbuckle, P. D.↗

DOE OSTI2025

AutoTandemML: Active Learning Enhanced Tandem Neural Networks for Inverse Design Problems

Inverse design in science and engineering involves determining optimal design parameters that achieve desired performance outcomes, a process often hindered by the complexity and high dimensionality of design spaces, leading to significant computational costs. To tackle this challenge, we propose a novel hybrid approach that combines active learning with Tandem Neural Networks to enhance the efficiency and effectiveness of solving inverse design problems. Active learning allows to selectively sample the most informative data points, reducing the required dataset size without compromising accuracy. We investigate this approach using three benchmark problems: airfoil inverse design, photonic surface inverse design, and scalar boundary condition reconstruction in diffusion partial differential equations. We demonstrate that integrating active learning with Tandem Neural Networks outperforms standard approaches across the benchmark suite, achieving better accuracy with fewer training samples.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Room temperature buffer gas beam of metastable state titanium atoms

We produce beams of neutral titanium (Ti) atoms in their metastable 3d3(F4)4sa5F5 state by laser ablation into He, N2, and Ar buffer gases. The high temperatures associated with the ablation process populate the a5F5 level without the need for optical pumping. Remarkably, we observe that Ti atoms in the a5F5 state survive thousands of collisions with He and Ar buffer gas atoms without being quenched to lower-energy states. We study the yield of Ti atoms when ablated into buffer gases of varying species and pressure, quantify quenching rates and diffusion cross sections based on simple models, and provide insight into optimal design parameters for an ablation cell. Using a 3.3 cm ablation cell with interchangeable exit apertures, we produce metastable atom beams and quantify their brilliance and velocity distributions as functions of buffer gas pressure.

Schrott, Jackson↗

DOE OSTI2020

MCP-PMT development at Argonne for particle identification

The proposed high-energy high-luminosity polarized Electron-Ion Collider (EIC) demands excellent particle identification over a wide range of particles momenta to achieve the best separation between signal and background particles. Various Cherenkov imaging detector sub-systems are being considered in EIC detector concepts for hadron identification for particles momenta up to 50 GeV/c. One important challenge in this case is to provide a reliable highly pixelated photosensor working in the high radiation and high magnetic field environment. The recently commercialized Large Area Picosecond Photo-Detector (LAPPD) provides a promising low-cost photosensor solution for the various EIC Cherenkov imaging sub-systems. Optimization of the phtosensor design for high magnetic field tolerance, precision timing resolution, and pixelated readout was performed at Argonne National Laboratory with 6 x 6 cm(2) microchannel plate photomultipliers. The techniques and optimized design parameters would be transferrable to industrial partners for low-cost LAPPD production to achieve the demonstrated performance.

atomic layer deposition↗

DOE OSTI2022

Deep Neural Network-Based Surrogate Model for Optimal Component Sizing of Power Converters Using Deep Reinforcement Learning

Not Available

42 ENGINEERING↗

DOE OSTI2020

NDX: Neutron Dose Rate Meters with Extended Capabilities

Particle accelerators, irradiation facilities, and nuclear power plants would benefit from using neutron dose rate meters featuring improved energy response covering full range of expected neutron energies, improved dynamic range of measured dose rates while providing the real-time data, and improved ability to operate in harsh radiation environments including heavy photon backgrounds and pulsed beams. The novel design of the neutron moderator for the NDX dose rate meter implements a layer of a Beryllium-loaded medium Z material which, similar to the earlier known WENDI detectors, allows the device to detect higher energy neutron flux and convert it to dose. Using Beryllium helps to fill the known dip in the response functions around 5-50 MeV. Optimized design parameter set, obtained using FLUKA Monte Carlo simulations, features the NDX moderator made of polyethylene embedding a layer of BeCu alloy inside, with the dose rate response constant within ±10% in the neutron energy range from about 100 keV to 500 MeV, and ±25% essentially in the full energy range above thermal. A new sensor technique implemented in the NDX is based on using the Ionization Chamber (IC) filled with 3He gas to capture the moderated neutron fluence, and includes a symmetric IC filled with regular 4He to evaluate the contributions due to the non-neutron ionizing radiation. Advantages of the method include large accessible dynamic range, relative insensitivity of the IC probes to photon radiation fields, and the ability to subtract their contribution. Two prototype NDX detectors were built, calibrated, and operated in various conditions at the CEBAF 12 GeV electron accelerator at JLab. The first results showed reliable neutron dose rate measurements in the presence of overwhelming photon radiation fields, and at practical high dose rate levels of up to approximately 10 Sv/h. Detector design, operation, first results, and further development plans are presented.

Degtiarenko, Pavel V.↗

DOE OSTI2025

Machine learning-driven design and self-sensing capabilities of automotive bumper lattices for adaptive impact response

We present a novel approach to design an automotive bumper energy absorber using carbon fiber reinforced polymer composites, optimized to meet conflicting performance requirements for two distinct impact scenarios. The design must satisfy both a low-speed (2.5 mph) pendulum intrusion test, simulating vehicle-to-vehicle collisions, and a high-speed (25 mph) leg flexion test, replicating pedestrian impacts. These tests demand opposing deformation characteristics: high flexibility (deformation < 85 mm) for the former and high stiffness (deformation < 22 mm) for the latter. To address these contradictory requirements, we developed a machine learning (ML) framework for inverse optimization of lattice designs and material selection. Unlike traditional iterative design processes, our ML model directly outputs optimal design parameters and material choices based on target performance inputs. The energy absorber was fabricated using advanced additive manufacturing techniques, including extrusion deposition and digital light processing. The integration of carbon fibers provides multifunctionality to the bumper structure, enabling self-sensing capabilities through changes in electrical resistivity under compression. This electrical response demonstrates high repeatability under multiple cycles at 2% compression and exhibits distinct signatures during crack formation under high deformation. This research offers adaptive performance through innovative design methodologies and smart material integration. The approach has potential applications in various fields requiring adaptive energy absorption and real-time structural health monitoring.

Chawla, Komal [ORNL] (ORCID:0000000190327565)↗

DOE OSTI2022

Cylindrical battery design app

Software that delivers optimal design parameters and performance predictions for cylindrical cells, which can range in size from microbatteries to EV batteries, is developed. The software utilizes machine learning and includes a graphical user interface to enable rapid prototyping and to accelerate energy storage research, development, and manufacturing. The Cylindrical battery design V1.0 comprises of three types of cylindrical batteries, Microbattery (Primary), Microbattery (Secondary) and 18650/21700/xxxxx Cylindrical battery. The software was developed in MATLAB. The software has the capability to output the cell design with the capacity ranges from several mAh to several million Ah.

Xiao, Jie↗

DOE OSTI2022

Machine Learning Software for Cylindrical Battery Design and Performance Prediction

A software that delivers optimal design parameters and performance predictions for cylindrical cells, which can range in size from micro batteries to EV batteries, is developed. The Cylindrical battery design V1.0 is comprised of three types of cylindrical batteries, Micro battery (Primary), Micro battery (Secondary) and 18650/21700/xxxxx cylindrical battery. The software was developed in MATLAB. The software has the capability to output the cell design with the capacity ranges from several mAh to several million Ah. The software utilizes machine learning and includes a graphical user interface to enable rapid prototyping to accelerate energy storage research, development, and manufacturing.

25 ENERGY STORAGE↗

DOE OSTI2023

Multiscale Porous High-temperature Heat Exchanger Using Ceramic Co-extrusion

In this project, our MIT, Purdue, and GE team aims to design, model, fabricate, and test a novel high temperature, compact, and durable ceramic heat exchanger to be operated under high temperature and pressure conditions for aerospace applications. Our approach is grounded in introducing multiscale porosity, i.e., centimeter-scale channels embedded with micrometer-scale channels, into the ceramic heat exchanger to significantly improve its heat transfer performance and mechanical strength while maintaining minimal pressure losses. We first developed high-fidelity thermal-fluid-mechanical model capable of precisely capturing the heat transfer rate, temperature profile, pressure drop, and mechanical stress throughout the entire heat exchanger design. Guided by our model, we identified the optimal design parameters for the SiC heat exchanger body and manifolds. Then, we established a completed fabrication procedure to create multiscale features in the ceramic heat exchanger, including co-extrusion, lamination, burnout, and sintering. We fabricated multiple heat exchanger bodies consisting of 6 × 6 and 3 × 3 centimeter-scale channels where each individual centimeter-scale channel comprises 625 crack-free microchannels with 90 μm × 90 μm opening. Owing to the multiscale features, our fabricated heat exchanger bodies exhibited desirable mechanical strength with 156 MPa flexural strength under 1300 Celsius degree. Despite the demonstrated highly tailorable microscopic features and superior mechanical strength, we identified delamination due to the complex interaction among ceramic, polymer, and gas species can be a critical challenge to create fully defect-free heat exchanger, which requires further fundamental investigations in future works. To test the heat exchanger performance, we constructed a high-temperature and high-pressure experimental apparatus that can be safely operated under 400 Celsius degree and 4 bar. With insights gained from mechanistic modeling, material development, and detailed characterization, a cost model was finally developed to understand the market potential of the developed technology, where a cost of $43,000 Celsius degree/kW was envisioned. This project developed a transformative approach to high-performance heat exchanger design. The thermal-fluid-mechanical design approach developed in this project can serve as a generic tool to guide the design of various heat-exchangers operated under high-temperature and high-pressure conditions. The material fabrication approach established in this project can be a useful guide for ceramic processing at extreme length scales.

42 ENGINEERING↗

DOE OSTI2026

Heat Pump Retrofits for Central Plant Hydronic Heating Systems: A Software Toolkit for Screening and Design

Retrofitting existing central plants with high-efficiency heat pump technologies can play a crucial role in achieving long-term planning goals. Modern heat pump technologies are able to use waste heat recovery to meet a building's heating demand, but there is a lack of accessible tools designed for non-HVAC experts, such as building owners, to quickly and easily conduct what-if analysis, e.g., estimating retrofit costs and payback period for their partial or full equipment replacement. This paper introduces an open-source software toolkit designed to facilitate the initial screening and decision-making of heat pump retrofits in existing central plants using a building's yearly load profile from metered or utility bill data. The toolkit evaluates the technical and economic viability of replacing traditional central plant equipment with various options including water-to-water or air-to-water heat pumps, which can provide efficient and lower-cost heating and cooling. It allows users to compare current central plant configurations with retrofit scenarios, assessing energy consumption, life-cycle costs, and environmental impact. The toolkit offers (1) a web-based tool designed for user-friendly access by a broad audience and (2) Python-based source code for researchers and engineers conducting parametric studies and design parameter optimization. The toolkit compares a typical central plant configuration to a configuration that uses a heat pump to supply hydronic heating and cooling. The output metrics include energy consumption and output of each equipment, life-cycle cost analyses and metrics, and environmental impact of the system.

Excell, L↗

NASA NTRS1973

Flight control systems research

Theoretical development is reported for the parameter optimization design technique needed for digital flight control system design. The results of an example case study applying the optimization technique for continuous systems to an F-8 aircraft feedback control system are presented. The concept of evolving the simplest system configuration that is capable of meeting a specified set of performance requirements is illustrated in this work.

Whitaker, H. P.↗

NASA NTRS1986

Development of a prototype automated on-orbit contact heat exchanger

An automated contact heat exchanger is being developed for use aboard the manned Space Station, serving as an interface heat exchanger between the pressurized module internal thermal buses and the central external thermal bus. The concept makes use of an array of flattened, thin-walled, flexible tubes that expand or contract to make or break the thermal connection as the internal pressure changes. Because of its simplicity, it permits on-orbit assembly by the remote manipulator system, thus eliminating the need for expensive EVA to make connections. A design methodology based on stress and thermal analyses has been developed and used to perform trade-offs between performance and cost, and to optimize design parameters. Simple verification tests have been performed to confirm the stress analysis model. Two conceptual variants of the contact heat exchanger are described, each designed for a 25 kW total heat load and a minimum uniform heat flux of 2.15 W/sq cm.

Lee, C. Y.↗