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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Utilizing digitized occurrence records of Midwestern feral Cannabis sativa to develop ecological niche models

Hemp (Cannabis sativa L.) has historically played a vital role in agriculture across the globe. Feral and wild populations have served as genetic resources for breeding, conservation, and adaptation to changing environmental conditions. However, feral populations of Cannabis, specifically in the Midwestern United States, remain poorly understood. This study aims to characterize the abiotic tolerances of these populations, estimate suitable areas, identify regions at risk of abiotic suitability change, and highlight the utility of ecological niche models (ENMs) in germplasm conservation. The Maxent algorithm was used to construct a series of ENMs. Validation metrics and MOP (Mobility-oriented Parity) analysis were used to assess extrapolation risk and model performance. We also projected the final projected under current and future climate scenarios (2021–2040 and 2061–2080) to assess how abiotic suitability changes with time. Climate change scenarios indicated an expansion of suitable habitat, with priority areas for germplasm collection in Indiana, Illinois, Kansas, Missouri, and Nebraska. This study demonstrates the application of ENMs for characterizing feral Cannabis populations and highlights their value in germplasm conservation and breeding efforts. Populations of feral C. sativa in the Midwest are of high interest, and future research should focus on utilizing tools to aid the collection of materials for the characterization of genetic diversity and adaptation to a changing climate.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Search for light mediators in the low-energy data of the CONNIE reactor neutrino experiment

The CONNIE experiment is located at a distance of 30 m from the core of a commercial nuclear reactor, and has collected a 3.7 kg-day exposure using a CCD detector array sensitive to an~1 keV threshold for the study of coherent neutrino-nucleus elastic scattering. Here we demonstrate the potential of this low-energy neutrino experiment as a probe for physics Beyond the Standard Model, by using the recently published results to constrain two simplified extensions of the Standard Model with light mediators. We compare the new limits with those obtained for the same models using neutrinos from the Spallation Neutron Source. Our new constraints represent the best limits for these simplified models among the experiments searching for CE$ν$NS for a light vector mediator with mass $ {M}_{Z^{\prime }} $< 10 MeV, and for a light scalar mediator with mass M$_{\phi}$< 30 MeV. These results constitute the first use of the CONNIE data as a probe for physics Beyond the Standard Model.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Search for coherent elastic neutrino-nucleus scattering at a nuclear reactor with CONNIE 2019 data

The Coherent Neutrino-Nucleus Interaction Experiment (CONNIE) is taking data at the Angra 2 nuclear reactor with the aim of detecting the coherent elastic scattering of reactor antineutrinos with silicon nuclei using charge-coupled devices (CCDs). In 2019 the experiment operated with a hardware binning applied to the readout stage, leading to lower levels of readout noise and improving the detection threshold down to 50 eV. The results of the analysis of 2019 data are reported here, corresponding to the detector array of 8 CCDs with a fiducial mass of 36.2 g and a total exposure of 2.2 kg-days. The difference between the reactor-on and reactor-off spectra shows no excess at low energies and yields upper limits at 95% confidence level for the neutrino interaction rates. In the lowest-energy range, 50 − 180 eV, the expected limit stands at 34 (39) times the standard model prediction, while the observed limit is 66 (75) times the standard model prediction with Sarkis (Chavarria) quenching factors.[graphic not available: see fulltext]

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

A coupled fluid-mechanical workflow to simulate the directed energy deposition additive manufacturing process

Simulation of additive manufacturing processes can provide essential insight into material behavior, residual stress, and ultimately, the performance of additively manufactured parts. In this work, we describe a new simulation based workflow utilizing both solid mechanics and fluid mechanics based formulations within the finite element software package SIERRA (Sierra Solid Mechanics Team in Sierra/Solid Mechanics 4.52 User’s Guide SAND2019-2715. Technical report, Sandia National Laboratories, 2011) to enable integrated simulations of directed energy deposition (DED) additive manufacturing processes. In this methodology, a high-fidelity fluid mechanics based model of additive manufacturing is employed as the first step in a simulation workflow. This fluid model uses a level set field to track the location of the boundary between the solid material and background gas and precisely predicts temperatures and material deposition shapes from additive manufacturing process parameters. Next, the resulting deposition shape and temperature field from the fluid model are then mapped into a solid mechanics formulation to provide a more accurate surface topology for radiation and convection boundary conditions and a prescribed temperature field. Solid mechanics simulations are then conducted to predict the evolution of material stresses and microstructure within a part. By combining thermal history and deposition shape from fluid mechanics with residual stress and material property evolutions from solid mechanics, additional fidelity and precision are incorporated into additive manufacturing process simulations providing new insight into complex DED builds.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Influence of fluorescent dopants on the vat photopolymerization of acrylate-based plastic scintillators for application in neutron/gamma pulse shape discrimination

Plastic scintillators, a class of solid-state materials used for radiation detection, were additively manufactured with vat photopolymerization. The photopolymer resins consisted of a primary dopant and a secondary dopant dissolved in a bisphenol A ethoxylate diacrylate-based matrix. The absorptive dopants significantly influence important print parameters, for example, secondary dopants decrease the light penetration depth by a factor > 12×. The primary dopant 2,5-diphenyloxazole had minimal impact on the printing process even when loaded at 25 % by mass of the resin. Working curve measurements, which relate energy dose to cure depth, were performed as a function of feature size to further assess the influence of dopants. Photopatterns smaller than 150 µm width had apparent increases in critical energy dose compared to larger photopatterns, while all resins maintained printed features in line gratings with 50 µm of separation. Printed scintillator monoliths were compared to scintillators cast by traditional molding, demonstrating that the layer-by-layer printing process does not decrease scintillation response. In conclusion, a maximum light output of 31 % of a benchmark plastic scintillator (EJ-200) and successful pulse shape discrimination were achieved with 20 % by mass 2,5-diphenyloxazole as the primary dopant and 0.1 % by mass 9,9-dimethyl-2,7-distyrylfluorene as the secondary dopant in printed scintillator samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Probing the surface of promoted CuO-Cr 2 O 3 -Fe 2 O 3 catalysts during CO 2 activation

The influence of basic oxide promoters on copper-chromium-iron oxide catalysts was investigated to determine the nature of surface oxygen species and structure-activity relationship for the reverse water-gas shift reaction. The catalysts were characterized with in situ XRD, in situ Raman, in situ XPS, in situ HS-LEIS and H 2 -TPR. Two surface oxygen sites with different reduction characteristics were found to be present. The overall CO 2 activation rate was found to correlate with both the number and reducibility of the more active oxygen species that were likely associated with the Cu-FeO x interfacial regions for enhanced hydrogen spillover. While addition of K 2 O somewhat preserved the interfacial regions and facilitated the reduction kinetics of surface oxygen, both Na 2 O and CaO significantly suppressed the availability of metallic Cu as well as the Cu-FeO x interfaces, leading to decreased reactivity. These findings provide a direction to promote the copper-iron catalysts by creating more metal-metal oxide interfacial sites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Effect of redox promoters (CeO x and CuO x ) and surface sulfates on the selective catalytic reduction (SCR) of NO with NH 3 by supported V 2 O 5 -WO 3 /TiO 2 catalysts

A series of TiO 2 -supported MO x catalysts (M=V, W, Ce, Cu and S) were investigated for their SCR activity. In situ Raman spectroscopy indicated that the supported MO x phases were completely dispersed as surface sites on the TiO 2 support. In situ IR revealed that surface VO x , WO x and SO x sites anchored at both CeO x /CuO x and TiO 2 sites. The number of surface Lewis acid sites decreased with the addition of basic (CeO x /CuO x ) and acidic (VO x /WO x ) sites in all catalysts, and acidic SO x in the unpromoted and Ce-promoted catalysts. The surface VO x , WO x and SO x sites introduced surface Brønsted acid sites. The redox promoters increased the NO conversion, but SO x impregnation inhibited their effect due to acid (SO x )-base (CeO x /CuO x ) interactions. Finally, the SCR reaction was shown to efficiently proceed via either surface NH 3 * or NH 4 +* species, resolving the long-standing dispute on the involvement of these species in the SCR reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

The effect of non-redox promoters (AlO x , PO x , SiO x and ZrO x ) and surface sulfates on supported V 2 O 5 -WO 3 /TiO 2 catalysts in selective catalytic reduction of NO with NH 3

The SCR activity of MO x (M=Al, P, Si, Zr) promoted V 2 O 5 -WO 3 /TiO 2 was investigated before and after sulfation. In situ IR spectroscopy indicated that the VO x active sites preferentially anchor on promoter generated surface hydroxyl. In situ Raman spectroscopy confirmed that all oxides are completely dispersed on the TiO 2 surface. In situ NH 3 -IR spectroscopy showed that the oxides can increase the Lewis (AlO x and ZrO x ) and Brønsted (PO x , SiO x , VO x , WO x and SO x ) acid site concentrations. The SiO x and ZrO x promoters had little effect on NO conversion, while the AlO x and PO x promoters and surface sulfation generally inhibited it. The SiO x promoted catalyst was highly SCR active despite lacking Lewis acid sites, indicating that they are not vital for SCR. Finally, the N 2 O formation activity of the catalyst was inhibited by surface sulfation and the promoters, correlating with the promoter and SO x induced increase in the Brønsted acid sites’ strength.

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

Advancing Building Energy Modeling with Large Language Models: Exploration and Case Studies

The rapid progression in artificial intelligence has facilitated the emergence of large language models like ChatGPT, offering potential applications extending into specialized engineering modeling, especially physics-based building energy modeling. This paper investigates the innovative integration of large language models with building energy modeling software, focusing specifically on the fusion of ChatGPT with EnergyPlus. A literature review is first conducted to reveal a growing trend of incorporating large language models in engineering modeling, albeit limited research on their application in building energy modeling. We underscore the potential of large language models in addressing building energy modeling challenges and outline potential applications including simulation input generation, simulation output analysis and visualization, conducting error analysis, co-simulation, simulation knowledge extraction and training, and simulation optimization. Three case studies reveal the transformative potential of large language models in automating and optimizing building energy modeling tasks, underscoring the pivotal role of artificial intelligence in advancing sustainable building practices and energy efficiency. The case studies demonstrate that selecting the right large language model techniques is essential to enhance performance and reduce engineering efforts. The findings advocate a multidisciplinary approach in future artificial intelligence research, with implications extending beyond building energy modeling to other specialized engineering modeling.

building energy modeling↗
DOE OSTI2025

Automatic building energy model development and debugging using large language models agentic workflow

Building energy modeling (BEM) is a complex process that demands significant time and expertise, limiting its broader application in building design and operations. While Large Language Models (LLMs) agentic workflow have facilitated complex engineering processes, their application in BEM has not been specifically explored. This paper investigates the feasibility of automating BEM using LLM agentic workflow. Here, we developed a generic LLM-planning-based workflow that takes a building description as input and generates an error-free EnergyPlus building energy model. Our robust workflow includes four core agents: 1) Building Description Pre-Processing, 2) IDF Object Information Extraction, 3) Single IDF Object Generator Suite, and 4) IDF Debugging Agent. These agents divide the complex tasks into manageable sub-steps, enabling LLMs to generate accurate and reliable results at each stage. The case study demonstrates the successful translation of a building description into an error-free EnergyPlus model for the iUnit modular building at the National Renewable Energy Laboratory. The effectiveness of our workflow surpasses: 1) naive prompt engineering, 2) other LLM-based workflows, and 3) manual modeling, in terms of accuracy, reliability, and time efficiency. The paper concludes with a discussion on the interplay between foundational models and LLM agent planning design, advocating for the use of fine-tuned, specialized models to advance this field.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Redefining fuel heating value for engines: Accounting for heat of vaporization

Defining a fuel's heating value (i.e., energy content) is fundamental for calculating engine efficiency and for life cycle analysis comparisons between different fuels. Traditional definitions of lower heating value and higher heating value account for the effect of water vapor versus liquid water in the exhaust, which is important when the fuel is used in a furnace or boiler. In an engine, it is equally important to properly account for the energy required to vaporize liquid fuel. Heat of vaporization has a small effect for common hydrocarbon fuels, typically less than 1% of lower heating value, but the effect is much larger for other important fuels such as ethanol (3.4% of lower heating value) and methanol (5.9% of lower heating value). This paper defines a new type of fuel heating value that more accurately reflects the useful fuel energy content for engines. Vaporized heating value is defined as the heating value when starting with a vaporized fuel instead of a liquid fuel. It can be calculated by adding the fuel's heat of vaporization to the traditional lower heating value. This paper illustrates the rationale and benefits of using vaporized heating value using data from the literature.

09 BIOMASS FUELS↗
DOE OSTI2024

Evaluation of methods for characterizing the fine particulate matter emissions from aircraft and other diffusion flame combustion aerosol sources

The U. S. Environmental Protection Agency in collaboration with the U. S. Air Force Arnold Engineering Development Complex conducted the VAriable Response In Aircraft nvPM Testing (VARIAnT) 3 and 4 test campaigns to compare nvPM emissions measurements from a variety of diffusion flame combustion aerosol sources (DFCASs), including a Cummins diesel engine, a diesel powered generator, two gas turbine start carts, a J85-GE-5 turbojet engine burning multiple fuels, and a Mini-CAST soot generator. The VARIAnT research program has conducted four test campaigns to date with the VARIAnT 3 and 4 test campaigns focusing on BC mass instrument performance, use of gas turbine engine sources for BC mass instrument calibration, and the characterization of the aerosols produced from the combustion sources. Results from both campaigns revealed agreement of about 20% between the AVL Micro-Soot Sensor, the Cavity Attenuated Phase Shift (CAPS PMSSA) monitor and the thermal-optical reference method for elemental carbon (EC), independent of the calibration source used. For the Artium LII-300, the measured mass concentrations in VARIAnT3 fall within 18% and in VARIAnT4 fall within 32% of the reference EC mass concentration when calibrated on a combustor rig in VARIAnT3 and on a LGT-60 start cart in VARIAnT4, respectively. It was also found that the three mass instrument types (MSS, CAPS PMSSA, and LII-300) can exhibit different BC to reference EC ratios depending on the emission source that appear to correlate to particle geometric mean mobility diameter, morphology, or some other parameter associated with particle geometric mean diameter (GMD) with the LII-300 showing a slightly stronger apparent trend with GMD. Systematic differences in LII-300 measured mass concentrations have been reduced by calibrating with a turbine combustion source (combustor or turbine engine). With respect to the particle size measurements made, the sizing instruments (TSI SMPS, TSI EEPS, and Cambustion DMS 500) were found to be in general agreement in terms of size distributions and concentrations with some exceptions. Teflon filter measurements of the total aerosol mass produced by the various DFCASs differed from the reference EC, BC, and integrated particle sized distribution measured aerosol masses. The Teflon filter measured mass was 30 to 40% greater than the reference EC and 50 to 60% greater than the BC mass for the J85 in both test campaigns. The measurements of particle size distributions and single particle analysis by miniSPLAT indicated the presence of large particles (>100 nm) having more compact morphologies, higher effective density, and a composition dominated by OC and ash. This increased large particle fraction is also associated with higher values of single scattering albedo measured by the CAPS PMSSA instrument and higher OC/EC measurements. These measurements indicate gas turbine engine emissions can be a more heterogeneous mix of particle types beyond the original E31 assumption that it is mainly composed of black carbon.

33 ADVANCED PROPULSION SYSTEMS↗