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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.

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At least 1,477 records · Page 82

Flight Acoustics Measurement Techniques and Applications

Careful consideration must be given to data acquisition and analysis techniques in the design of experiments for the measurement of noise generated by flight vehicles. Although noise measurement locations and data reduction procedures are specified for aircraft certification by FAA and ICAO directives, for example, there are virtually no established procedures for aircraft noise measurement for other purposes. To optimize the quality and quantity of information obtained in a flight acoustics experiment, microphone layout, data acquisition, and analysis must be tailored to the specific test objective. This paper will review flight acoustics technology at NASA Langley Research Center developed over the past decade. In particular, the paper will focus on flight experiments performed for three diverse objectives: (1) research applications, such as noise prediction code validation, (2) noise impact modeling, and (3) noise abatement flight procedures. To best achieve these diverse objectives, different deployments of microphone systems on the ground are required, and different data analysis techniques are needed. In all cases, accurate positioning of the aircraft synchronized in time with the data recording is necessary. However, there are some restrictions on flight operations unique to each case for the methods to properly work.

Preisser, J. S.↗

Optimizing the NASA Technical Report Server

The NASA Technical Report Server (NTRS), a World Wide Web report distribution NASA technical publications service, is modified for performance enhancement, greater protocol support, and human interface optimization. Results include: Parallel database queries, significantly decreasing user access times by an average factor of 2.3; access from clients behind firewalls and/ or proxies which truncate excessively long Uniform Resource Locators (URLs); access to non-Wide Area Information Server (WAIS) databases and compatibility with the 239-50.3 protocol; and a streamlined user interface.

Nelson, Michael L.↗

NUclear Measurement System Optimization

The NUclear Measurement System Optimization (NUMSO) toolbox interfaces with models developed using SGA to provide combined uncertainty and related operations information about the safeguards process. The primary focus of NUMSO is to determine the best locations and operating times for measurement devices to minimize the sum of Type I and Type II errors. A secondary focus is to determine the key contributors to the Type I and Type II errors indicated by SGA. NUMSO can also determine the best devices to recalibrate and the best times to recalibrate those devices given a limited budget.

Johnson, Benjamin↗

Remote Radiation Sensing Using Aerial and Ground Platforms

Remote sensing of ionizing radiation has a significant role in waste management, nuclear material management and nonproliferation, and radiation safety. Robotic platforms can surpass the number of tasks that are achieved by humans. With this technique, the operator's radiation exposure can be decreased. Remote sensing allows for the evaluation and monitoring of radiological contamination. Gamma-ray and neutron sensors were integrated onto the robotic platforms. This approach allows for the radiation sensor data to be dynamically tracked and mapped thus enabling further analysis of the radiation flux in temporal and spatial domains. The goal is to complete scheduled tasks while the robot is being irradiated. To achieve this, electronic components must be shielded and radiation hardened. CZT Detector: Cadmium Zinc Telluride (CZT) detector technology has been a promising solution for gamma-ray and x-ray measurements. Detector data is transferred to the Odroid minicomputer that controls and powers the module via the USB. Robot Operating System (ROS) was utilized for data acquisition and data fusion. The Mariscotti method was employed for the spectrum analysis. A function was programmed in ROS for the automatic identification of photopeaks. CLYC Detector: A Cs{sub 2}LiYCl{sub 6}:Ce{sup 3+} (CLYC) detector was used for simultaneous medium-resolution gamma-ray measurements and neutron counting. A 2.54 cm diameter photomultiplier tube (PMT) was equipped with a high voltage supply and a miniature digitizer. Gamma-ray excitation: fast core-to-valence luminescence (CVL) with 1 ns decay constant, and prompt Ce{sup 3+} emission with 50 ns decay constant. Neutron excitation: slow cerium self-trapped excitation (Ce{sup 3+} STE), 1000 ns decay constant. Radiation Source Localization: Maximum Likelihood Estimation (MLE) and gradient-based methods were used to locate the position of a radiation source based on measured radiation intensities. Multi-Particle Transport Code FLUKA: Estimation of radiation damage of the electronic components is important in order to optimize the robot's operational time while it is irradiated. Displacement per atom (DPA) represents the radiation damage in materials exposed to the ionizing radiation. Various shielding layers of different thickness t were analyzed (< 5% statistical error). The model of the controller of the UAS was designed in FLUKA. Conclusion: CZT and CLYC detectors were integrated onto the robotic platforms. Radiation source localization and contour mapping using robotic platforms were studied. Functions for data analysis and fusion were developed in ROS. FLUKA code was utilized to analyze DPA values. Layers of low-density and high-density materials were used to shield the UAS electronics.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

HybridSystemsSimulations.jl - Solving the Merchant Collocated Facilities with JuMP

The development of new clean-generation technologies also leads to new plant-level architectures that combine several generation and storage assets behind the point of connection. These co-located generation resources (Hybrid Systems) primarily operate as merchant assets that employ automated market bidding models and internal Energy Management Systems (EMS) to comply with the operator's signals. Formulating an optimal bidding model requires embedding the EMS control model into the bidding algorithm, resulting in a bi-level optimization problem. In this presentation, we first showcase using JuMP to formulate and solve this problem effectively for multiple merchant systems and the bidding outcomes considering different model formulations. Second, the bidding outcomes are later integrated into a PowerSimulations.jl (also built with JuMP) simulation to study the system-level effects of the various merchant bidding and the interactions between market-clearing models and the embedded EMS model. We will showcase simulations conducted in the RTS system considering different levels of merchant hybrid systems participation. The presentation provides the following specific insights on JuMP usage: 1) the Formulation of specialized bi-level problems with custom cuts to solve the merchant hybrid system bidding problem; 2) the integration of a modular model within a complex simulation workflow supported by JuMP in PowerSimulations.jl; 3) Accelerating the solution of power systems operations simulation that employ agent optimization problems using JuMP.

energy markets↗

Neutron-producing gas puff Z-pinch experiments on a fast, low-impedance, 0.5 MA linear transformer driver

A study on the neutron production from single and double gas puff Z-pinches on the CESZAR linear transformer driver with ~0.45 MA current and 170 ns rise time is presented. Total neutron yield measurements made with a LaBr activation detector are compared for three configurations, using a double nozzle setup. When a single, hollow, deuterium gas shell was used, reliable implosions could only be attained at higher load mass than the optimal value to match implosion time with the driver rise time, with neutron yields of ~10 6 per pulse. The use of a double gas puff configuration with a deuterium center jet allowed a reduction in the shell density and operation closer to machine-matched conditions, recording up to (4.1 ± 0.3) × 10 7 neutrons/pulse when either Kr or D 2 was used in the shell. For a comparable mass and implosion time, using a higher atomic-number gas in the outer shell results in more unstable plasma surface and smaller plasma radius at the location of instability bubbles, which, however, do not seem to consistently correlate with a higher neutron yield. Comparing implosion dynamics with models and neutron yields with literature scaling suggests that the machine current is not well coupled to the plasma during the final stages of compression. Optimizing current and energy coupling to the pinched plasma is critical to improving performance, particularly in low-impedance drivers.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Enabling Next Generation Reaction Injection Molding (RIM) for Lightweight Structures

Replacing metal components in trucks, trailers, and buses with lightweight polymer composites is challenging due to high temperatures and complex manufacturing. The Reaction Injection Molding (RIM) process using Dicyclopentadiene (DCPD) resin offers a solution by producing robust parts with excellent stiffness, impact strength, and resistance properties. Simulations are essential for optimizing this process, predicting defects, and improving quality. However, most commercial software is tailored for thermoplastics, requiring thermoset users to generate their own datasets. In this project, a material data card for DCPD was developed to perform RIM simulations. Design of Experiments (DOE) was used to identify key factors affecting filling, curing, and warpage, aiming to minimize cycle time and defects. The simulations explored varying injection gate parameters (size, location, number) and process conditions (mold/resin temperature, injection/curing pressure). Results showed that gate design significantly impacts filling behavior and defects. A single central gate provided balanced flow with fewer defects, while two corner gates led to more defects. Additionally, lower injection pressure increased filling time, while higher mold temperature accelerated curing but led to more warpage. This optimization framework aims to enhance DCPD part performance and promote sustainable manufacturing by reducing waste and energy consumption. This research has been performed in collaborations with McClarin Composites. The research outcome has been submitted to the Journal of Manufacturing Processes.

36 MATERIALS SCIENCE↗

Using Robotic Manipulators for Radioactive Waste Inspection - 20090

The global nuclear industry has a growing volume of nuclear waste which needs to be scanned, sorted according to its activity and material type, then processed into the correct waste packages for long term storage and disposal. It is vital that there is a detailed understanding of the waste inventory stored in long term waste containers, as knowledge of their contents could predict or prevent any adverse effects in storage. The numerous 'scan and sort' tables which are currently used at many different facilities around the world to sort waste into their correct containers are human operated and require very slow gamma scanning procedures combined with educated guesswork to manually sort the waste. This often leads to excessive conservatisms, with placement of lower activity wastes in higher activity containers, which in turn costs significantly more to store. In the United Kingdom it costs UK Pounds 46 k per cubic meter to store intermediate level waste compared to just UK Pound 2.9 k per cubic meter to store low level waste according to a 2008 Department of Energy and Climate Change report in the UK. A proposed solution to this problem, is the use of a robotic manipulator to automatically inspect the 'scan and sort table' in order to produce an accurate 3D model of the table's waste contents and attach an overlaid radiation map. The radiation map contains spectrometry data and can in consequence be used to distinguish and locate specific radioisotopes. The 3D model should be as accurate as possible in order to allow for a second robot arm with an attached gripper to grasp the objects and place them into their designated long-term storage container. Various scanning procedures are explored in this study including basic raster scanning, adaptive raster scanning and point sampling. The optimal solution will in practice be defined by the required application and activity level of the wastes being inspected. The results presented in this study indicate that it is possible to produce a centimeter accurate 3D model of a mixed assortment of components on a nuclear waste 'scan and sort' table. In addition, it was shown that the waste objects emitting radiation could be accurately identified and located, with an overlaid radiation map. This study is applicable across the nuclear waste management sector. Many of the ideas and concepts developed in this study are applicable in other decommissioning settings for example, dismantling of legacy gloveboxes or routine inspection of nuclear waste packages in storage. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Optimizing group structures using hierarchical division

Creating group structures with few groups that give low errors is a difficult problem in reactor analysis. In recent years, automated optimization techniques have been applied to this task. We continue this trend by applying the hierarchical division algorithm to generate optimized group structures that minimize a cost function. At each stage, the algorithm adds a single group boundary to an existing group structure, dividing one group into two to increase the resolution of the group structure. The location of the added boundary is the one that gives the lowest error over all possible new boundary locations. Our implementation requires a beginning group structure, a set of candidate new boundary locations, and a set of reference reaction rates. As a proof of concept, we used WIMS-69 as the initial group structure, XMAS-172 as the ending group structures, and a 344-group reference group structure. Testing on two simple, homogenized reactor problems, we found that hierarchical division was able to reduce the error by a factor of around 5 with an increase of only 15% in the number of groups. Because hierarchical division can get stuck in local minima, it often reaches a plateau in its error reduction capability as many groups are added. Nevertheless, we find hierarchical division has strong potential to make good group structures into great group structures at a modest increase in computational cost. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Feature Based Qualification of 17-4PH Stainless Steel to Evaluate Location-Specific Variability in Wire Arc Additive Manufacturing

Qualifying large-scale metal additive manufacturing (M-AM) technologies such as wire arc additive manufacturing (WAAM) can be challenging. This is especially significant in precipitation hardened martensitic stainless steels like SS 17-4PH, where thermal histories induce location-specific microstructural variability and property anisotropy. The Department of Defense (DOD) and the United States Army Combat Capabilities Development Command Ground Vehicle Systems Center (GVSC) Ground Vehicle Materials Engineering (GVME) aim to build robust and qualified large-scale M-AM workflows that could reduce the time and cost through quick and informed evaluation, testing, and development of feedstock, processes, and parts. The report presents the findings from the collaborative efforts between Oak Ridge National Laboratory (ORNL) and the U.S. Army GVSC GVME. The aim of this project was to develop a geometric feature-based qualification framework for WAAM of SS 17-4PH components. This report outlines selection methodology of representative build geometries, optimization of WAAM process parameters, in-situ monitoring, microstructure-property evaluation, thermal simulations, as well as data visualization techniques incorporated in this project. The results from this project demonstrate a clear understanding of thermal history dependent phase evolution and consequent location-specific property variations in WAAM of SS 17-4PH. These results in conjunction with the data-driven methodologies used in this project are expected to reduce qualification timelines, improve predictability, and accelerate the development of reliable feature-based qualification strategies for part production via large-scale M-AM technologies.

36 MATERIALS SCIENCE↗

Parametric and sensitivity analysis of a PCM-integrated wall for optimal thermal load modulation in lightweight buildings

Load modulation in buildings is becoming increasingly important due to growing disparity in energy demand during peak and off-peak hours. Integrating phase change material (PCM) in building envelopes and using a controlled precooling strategy can provide substantial thermal load modulation; however, it may greatly increase the total energy use. Previous studies have employed PCM in building envelopes primarily for energy savings and, to some extent, peak load shedding and shifting. However, the load modulation capacity of a PCM-integrated envelope has not been well explored in the literature. In this study, we perform an extensive parametric and sensitivity analysis on PCM-integrated lightweight building walls and examine the combinatory effects of various PCM parameters on thermal load modulation and wall-related heat gains in buildings. Using numerical simulations, we investigate eight PCM parameters: PCM location in the wall, transition temperature, thickness, latent heat, transition range, density, specific heat, and thermal conductivity. Here, we evaluate their impact and relative importance to achieve maximum load modulation in buildings without compromising occupants’ thermal comfort or total energy use. The results show that the optimized PCM proposed in this study can completely invert the transient heat gain profile of the wall, providing up to 70% reduction of wall-related heat gain during peak hours without a major increase in the cumulative heat gain.

42 ENGINEERING↗

PVDeg: Enhancing Usability and AI-Driven Multi-Mechanism Degradation Modeling

PVDeg version 0.7.0, released in December 2025, introduced major enhancements to improve usability and performance. This update reorganized tutorials and tool notebooks to create a more intuitive experience, enabling users to easily follow and adapt workflows for their specific analyses. In addition to structural improvements, both the notebooks and core logic underwent significant optimization for efficiency, robustness, and style. These refinements were supported by new testing frameworks built on nbval and pytest, adherence to PEP8 standards, and extensive code refactoring, which collectively simplify onboarding for new developers. Looking ahead, version 0.8.0 will deliver advanced AI-driven capabilities. The primary focus is to further develop and automate the degradation workflow, designed to analyze PV module degradation across diverse locations and system configurations. By integrating large language models (LLMs) to scan literature and compile a comprehensive database of materials and degradation rates, this feature will enable modeling of multiple materials and mechanisms within a single, streamlined workflow. Users will be able to evaluate degradation impacts on different system architectures under varying environmental conditions, facilitating informed decisions on bill-of-materials optimization for specific deployment scenarios. These advancements position PVDeg as a powerful, user-friendly tool for accelerating PV reliability research and system design.

14 SOLAR ENERGY↗

Simulation-driven design optimization of reaction injection molding (RIM) process for polydicyclopentadiene (pDCPD): Minimizing cycle time, defects, and warpage

Replacing metal components in trucks, trailers, and buses with lightweight polymer composites is challenging due to high temperatures and complex manufacturing. The Reaction Injection Molding (RIM) process using Dicyclopentadiene (DCPD) resin offers a solution by producing robust parts with excellent stiffness, impact strength, and resistance properties. Simulations are essential for optimizing this process, predicting defects, and improving quality. However, most commercial software is tailored for thermoplastics, requiring thermoset users to generate their own datasets. In this study, a material data card for DCPD was developed to perform RIM simulations. Design of Experiments (DOE) was used to identify key factors affecting filling, curing, and warpage, aiming to minimize cycle time and defects. The simulations explored varying injection gate parameters (size, location, number) and process conditions (mold/resin temperature, injection/curing pressure). Results showed that gate design significantly impacts filling behavior and defects. A single central gate provided balanced flow with fewer defects, while two corner gates led to more defects. Additionally, lower injection pressure increased filling time, while higher mold temperature accelerated curing but led to more warpage. In conclusion, this optimization framework aims to enhance DCPD part performance and promote sustainable manufacturing by reducing waste and energy consumption.

42 ENGINEERING↗

Capacitated p -hub approach for park-and-ride facility location problem under nested logit demand function: polyhedral approaches

By generalizing the unconstrained p-hub approach for the park-and-ride (P&R) facility location problem under the multinomial logit demand function, the capacitated p-hub approach for the problem under the nested logit demand function captures a broader range of real-world cases. To solve this problem optimally, we introduce a mixed-integer linear program and accelerate its solution by enhancing the branch-and-cut procedure. To address the problem at a large scale, we introduce two other polyhedral approaches: variable neighborhood search (VNS) and adaptive randomized rounding (ARR). Downtown areas in Seoul have a high modal share of public transportation and congested road traffic, yet P&R has not been widely implemented. Therefore, we apply the ARR procedure to solve a real-world problem using traffic and geographic data from the Seoul metropolitan area. ARR performs better than VNS and addresses real-world cases. The solutions obtained by ARR present a phased expansion plan that encourages policymakers to start installing a small number of P&Rs immediately.

Capacitated p-hub approach↗

Model for Characterization and Optimization of Spectrally Selective Structures to Reduce the Operating Temperature and Improve the Energy Yield of Photovoltaic Modules

Many existing commercially manufactured photovoltaic modules include a cover layer of glass, commonly coated with a single layer antireflection coating (ARC) to reduce reflection losses. As many common photovoltaic cells, including c-Si, CdTe, and CIGS, decrease in efficiency with increasing temperature, a more effective coating would increase reflection of sub-bandgap light while still acting as an antireflection coating for higher energy photons. The sub-bandgap reflection would reduce parasitic sub-bandgap absorption and therefore reduce operating temperature. This reduction under realistic outdoor conditions would lead to an increase in annual energy yield of a photovoltaic module beyond what is achieved by a single layer ARC. However, calculating the actual increase in energy yield provided by this approach is difficult without using time-consuming simulation. Here, we present a time-independent matrix model which can quickly determine the percentage change in annual energy yield of a module with a spectrally selective mirror by comparison to a baseline module with no mirror. The energy benefit is decomposed into a thermal component from temperature reduction and an optical component from increased transmission of light above the bandgap and therefore increased current generation. Time-independent matrix model calculations are based on real irradiance conditions that vary with geographic location and module tilt angle. The absolute predicted values of energy yield improvement from the model are within 0.1% of those obtained from combined ray-tracing and time-dependent finite-element simulations and compute 1000x faster. Uncertainty in the model result is primarily due to effects of wind speed on module temperature. Optimization of the model result produces a 13-layer and a 20-layer mirror, which increase annual module energy yield by up to 4.0% compared to a module without the mirror, varying depending on the module location and tilt angle. Finally, we analyze how spectrally selective mirrors affect the loss pathways of the photovoltaic module.

14 SOLAR ENERGY↗

I 2 S-LWR microchannel heat exchanger design and experimental validation

The Integral Inherently Safe Light Water Reactor (I 2 S-LWR) includes primary-to-secondary coolant heat exchangers located in the downcomer of the reactor pressure vessel. A microchannel heat exchanger (MCHX) configuration is selected to meet the limited available volume and high heat duty requirements. The design, modeling, and optimization of the liquid-liquid MCHX is outlined. In addition, the performance of a MCHX test section representative of the I 2 S-LWR MCHX design is validated experimentally. Experimental results show that heat transfer and pressure drop correlations developed for larger, macroscale channels lead to accurate predictions of performance. Additionally, this study shows that an MCHX can deliver the required heat duties within the available space and pressure drop constraints of the overall I2 S-LWR design.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The geospatial and economic viability of CO 2 storage in hydrocarbon depleted fractured shale formations

Hydrocarbon depleted fractured shale (HDFS) formations could be attractive for geologic carbon dioxide (CO 2 ) storage. Shale formations may be able to leverage existing infrastructure, have larger capacities, and be more secure than saline aquifers. We compared regional storage capacities and integrated CO 2 capture, transport, and storage systems that use HDFS with those that use saline aquifers in a region of the United States with extensive shale development that overlies prospective saline aquifers. We estimated HDFS storage capacities with a production-based method and costs by adapting methods developed for saline aquifers and found that HDFS formations in this region might be able to store with less cost an estimated ~14× more CO 2 on average than saline aquifers at the same location. The potential for smaller Areas of Review and less investment in infrastructure accounted for up to 84% of the difference in estimated storage costs. We implemented an engineering-economic geospatial optimization model to determine and compare the viability of storage capacity for these two storage resources. Across the state-specific and regional scenarios we investigated, our results for this region suggest that integrated CCS systems using HDFS could be more centralized, require less pipelines, prioritize different routes for trunklines, and be 6.4–6.8% ($5-10/tCO 2 ) cheaper than systems using saline aquifers. In conclusion, overall, CO 2 storage in HDFS could be technically and economically attractive and may lower barriers to large scale CO 2 storage if they can be permitted.

42 ENGINEERING↗

On the marginal value of electricity storage

We investigate the problem of characterizing the economic value of energy storage capacity to a wind power producer (WPP) that sells its energy in a conventional two-settlement electricity market. The WPP can offer a forward contract to supply power in the day-ahead market, subject to financial penalties for imbalances between the contracted power and the power that is delivered in real-time. We consider the setting in which the WPP has access to a co-located energy storage system, and can thus reshape its wind power production subject to its storage capacity constraints. Modeling wind power as a random process, we show that the problem of determining optimal forward contract offerings—given recourse with storage—is convex. We further establish that the maximum expected profit is concave and non-decreasing in the energy storage capacity, which reveals that the greatest marginal benefit from energy storage is derived from initial investment in small storage capacity. We provide a characterization of the marginal value of small energy storage capacity to the WPP. The formulae we derive shed light on the relationship between the value of storage and certain statistical measures of variability in the underlying wind power process.

25 ENERGY STORAGE↗