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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 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Experimental investigation on multiscale hydrodynamics in a novel gas–Liquid–Solid three phase jet-Loop reactor

Multiphase flow hydrodynamics in a novel gas–liquid–solid jet-loop reactor (JLR) were experimentally investigated at the macroscales and mesoscales. The chord length distribution was measured by an optical fiber probe and transformed for bubble size distribution through the maximum entropy method. The impacts of key operating conditions (superficial gas and liquid velocity, solid loading) on hydrodynamics at different axial and radial locations were comprehensively investigated. JLR was found to have good solid suspension ability owing to the internal circulation of bubbles and liquid flow. The gas holdup, axial liquid velocity, and bubble velocity increase with gas velocity, while liquid velocity has little influence on them. Compared with the gas–liquid JLRs, solids decrease the gas holdup and liquid circulation, reduces the bubble velocity and delays the flow development due to the enhanced interaction between bubbles and particles (Stokes number >1). This work also provides a benchmark data for computational fluid dynamics (CFD) model validation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Large metastability in Cu (In,Ga)Se 2 devices: The importance of buffer properties

Some commercial Cu (In,Ga)Se 2 (CIGS) modules reveal large changes in current-voltage parameters with light soaking. While such changes are not necessarily indicative of a performance problem, the associated uncertainty may be disadvantageous in a highly competitive market. Thus, it is beneficial to understand the origin of large metastabilities in order to define what processing changes might diminish metastability without impacting other desirable aspects of high-performance devices. This report attempts to reproduce large metastabilities like those in some commercial products both through absorber and buffer processing variations in small devices. While variations of both types were found to affect metastability, only buffer variations could reproduce large metastability in high-efficiency devices. Device modeling validates that buffer effects alone are sufficient to explain the large metastability seen in these devices.

14 SOLAR ENERGY↗
DOE OSTI2023

Extinction Imaging Diagnostics for In Situ Quantification of Soot within Explosively Generated Fireballs

Fireballs produced from the detonation of high explosives often contain particulates primarily composed of various phases of carbon soot. The transport and concentration of these particulates is of interest for model validation and emission characterization. Here, this work proposes ultra-high-speed imaging techniques to observe a fireball's structure and optical depth. An extinction-based diagnostic applied at two wavelengths indicates that extinction scales inversely with wavelength, consistent with particles in the Rayleigh limit and dimensionless extinction coefficients which are independent of wavelength. Within current confidence bounds, the extinction-derived soot mass concentrations agree with expectations based upon literature reported soot yields. Results also identify areas of high uncertainty where additional work is recommended.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Search for excited $τ$-leptons and leptoquarks in the final state with $τ$-leptons and jets in pp collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

A search is reported for excited $τ$-leptons and leptoquarks in events with two hadronically decaying $τ$-leptons and two or more jets. The search uses proton-proton ($pp$) collision data at $\sqrt{s}$ = 13 TeV recorded by the ATLAS experiment during the Run 2 of the Large Hadron Collider in 2015–2018. The total integrated luminosity is 139 fb -1 . The excited $τ$-lepton is assumed to be produced and to decay via a four-fermion contact interaction into an ordinary $τ$-lepton and a quark-antiquark pair. The leptoquarks are assumed to be produced in pairs via the strong interaction, and each leptoquark is assumed to couple to a charm or lighter quark and a $τ$-lepton. No excess over the background prediction is observed. Excited $τ$-leptons with masses below 2.8 TeV are excluded at 95% CL in scenarios with the contact interaction scale Λ set to 10 TeV. At the extreme limit of model validity where Λ is set equal to the excited $τ$-lepton mass, excited $τ$-leptons with masses below 4.6 TeV are excluded. Leptoquarks with masses below 1.3 TeV are excluded at 95% CL if their branching ratio to a charm quark and a $τ$-lepton equals 1. The analysis does not exploit flavour-tagging in the signal region.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Harnessing Machine Learning to Predict MoS 2 Solid Lubricant Performance

Physical vapor deposited (PVD) molybdenum disulfide (MoS 2 ) solid lubricant coatings are an exemplar material system for machine learning methods due to small changes in process variables often causing large variations in microstructure and mechanical/tribological properties. Here, in this work, a gradient boosted regression tree machine learning method is applied to an existing experimental data set containing process, microstructure, and property information to create deeper insights into the process-structure–property relationships for molybdenum disulfide (MoS 2 ) solid lubricant coatings. The optimized and cross-validated models show good predictive capabilities for density, reduced modulus, hardness, wear rate, and initial coefficients of friction. The contribution of individual deposition variables (i.e., argon pressure, deposition power, target conditioning) on coating properties is highlighted through feature importance. The process-property relationships established herein show linear and non-linear relationships and highlight the influence of uncontrolled deposition variables (i.e., target conditioning) on the tribological performance.

MoS2↗
DOE OSTI2024

Fuel performance analysis of Cr-coated Zircaloy-4 cladding during a prototypical LOCA event using BISON

Here, deformation and failure of chromium (Cr) coated Zircaloy-4 (Zry-4) were studied in loss-of-coolant accident (LOCA) conditions using the BISON fuel performance code. The BISON validation model simulating Halden research reactor experiments was extended to include Cr coatings and higher rod internal pressures to simulate high-burnup fuel. The transient simulations show Cr coatings help relieve stress in the Zry-4 substrate during the transient, delaying the onset of high-temperature creep, which leads to ballooning and bursting of the cladding. A nominal Cr coating thickness of 30 µm delays clad failure by 26 seconds and increases the clad burst temperature by 40 K. A parametric study showed that time to failure and burst temperature both increase with coating thickness, and Cr-coated cladding offers burst resistance under a wide range of rod internal pressures simulating high-burnup fuel. Results indicate that a thin Cr coating provides resistance against ballooning and bursting of cladding during LOCA events.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

A numerical investigation on methane combustion and emissions from a natural gas-diesel dual fuel engine using CFD model

Natural gas (NG)-diesel dual fuel engines have been criticized for their high emissions of unburned methane. The past research on methane emissions from dual fuel engines has focused on the measurement of methane concentration in exhaust gases. The development of approaches capable of minimizing methane emissions requests the detailed spatial distribution of methane in-cylinder during the combustion and post combustion processes. However, it is difficult to experimentally measure the spatial distribution of methane in-cylinder. Here this research presents a numerical study on the combustion process of a NG-diesel dual fuel engine using the computational fluids dynamics (CFD) model CONVERGE coupled with a reduced primary reference fuel (PRF) mechanism. The model was validated against the heat release process and the emissions of nitrogen oxide, methane and carbon monoxide measured in a single cylinder dual fuel engine. The validated CFD model was applied to investigate the combustion of methane and n-heptane and the spatial distribution of methane in the dual fuel engine. This is most likely the first attempt to visualize the spatial distribution of methane in dual fuel engines using CFD. The objective of this study is to numerically simulate the methane combustion process, especially the methane present outside the pilot spray, quantify the methane combustion in each combustion stage, and visualize the spatial methane distribution in cylinder. The results showed that the momentum produced by the pilot fuel injection and combustion pushed the combustion products of pilot fuel and methane within the pilot spray plume toward the unburned methane-air mixture. Such a movement enhanced the mixing of the hot combustion products and the relatively cold unburned methane-air mixture during the main combustion process and dominated the combustion of methane presented outside the pilot fuel spray plume. Based on the simulation results at a low load condition (4.05 bar), the main combustion process consumed 43–53% of the methane fumigated into the intake mixture. The post-combustion oxidation process consumed 17–29% of the intake methane, which was 36.2–51.8% methane that survived the main combustion process. In comparison, 27–35% methane emitted the engine without participating the combustion process. The unburned methane at exhaust valve opening was mainly observed at the center of the cylinder. In comparison, the contribution of the crevice and boundary layer around the cylinder liner to methane emissions was relatively small. The slip of methane through the dual fuel engines was due to the fact that the premixed mixture was too lean to support the propagation of the turbulent flame initiated by the pilot fuel and the lack of pilot fuel vapor reaching the center of the combustion chamber because of the geometric limitations of the fuel injection system and the reduced mass of pilot fuel injected into the cylinder. The approaches aiming to enhance the combustion of methane and minimize methane emissions from dual fuel engines should focus on those capable of increasing the volume of pilot fuel vapor formed after injected into the cylinder.

42 ENGINEERING↗
DOE OSTI2018

Experimental evaluation and thermodynamic system modeling of thermoelectric heat pump clothes dryer

Electric clothes dryers consume about 6% of US residential electricity consumption. Using a solid-state technology without refrigerant, thermoelectric (TE) heat pump dryers have the potential to be more efficient than units based on electric resistance and less expensive than units based on vapor compression. This study presents a steady state TE dryer model, and validates the model against results from an experimental prototype. The system model is composed of a TE heat pump element model coupled with a psychrometric dryer sub-model. Experimental results had energy factors (EFs) of up to 2.95 kg of dry cloth per kWh (6.51 lb c /kWh), with a dry time of 159 min. A faster dry time of 96 min was also achieved at an EF of 2.54 kg c /kWh (5.60 lb c /kWh). The model was able to replicate the experimental results within 5% of EF and 5% of dry time values. Finally, the results are used to identify important parameters that affect dryer performance, such as relative humidity of air leaving the drum.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Performance evaluation of a metamaterial-based new cool roof using improved Roof Thermal Transfer Value model

A new cool roof with potential to generate significant energy savings in buildings has been developed from a metamaterial film named as RadiCold. Considering that the RadiCold film has unique optical and thermal characteristics and the current Roof Thermal Transfer Value model neglecting the effect of roof thermal mass that may lead to overestimating the cooling load from roofs, this work developed an improved Roof Thermal Transfer Value model and validated the model for both RadiCold cool roof and traditional roofing structures. Data from the reduced-size model building experiments showed that the improved Roof Thermal Transfer Value model can accurately describe the heat gains or losses via the roofs. Under real-world weather conditions in the United States (Tucson AZ, Los Angeles, CA, and Orlando FL), the improved Roof Thermal Transfer Value model has been applied to three types of roof exterior finishing: shingle, Thermoplastic Polyolefin (a cool roof material) and RadiCold. In a typical meteorology year, the modeling results show that the shingle and Thermoplastic Polyolefin roof transfer 78.9–294.1 kWh/(m 2 ·yr) and 8.5–128.2 kWh/(m 2 ·yr) of heat into the building space, respectively, but the RadiCold cool roof dissipates 137.6–268.7 kWh/(m 2 ·yr) of heat from the building space to outdoor environment (e.g., sky). The cooling load reduction from utilizing RadiCold cool roof results in cooling electricity savings of 113.0–143.9 kWh/(m 2 ·yr) compared to the shingle roof and 88.0–92.4 kWh/(m2·yr) compared to the Thermoplastic Polyolefin roof for the three analyzed locations with an assumed air conditioning system’s coefficient of performance of 3.0.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Performance evaluation of an agent-based occupancy simulation model

Occupancy is an important factor driving building performance. Static and homogeneous occupant schedules, commonly used in building performance simulation, contribute to issues such as performance gaps between simulated and measured energy use in buildings. Stochastic occupancy models have been recently developed and applied to better represent spatial and temporal diversity of occupants in buildings. However, there is very limited evaluation of the usability and accuracy of these models. This study used measured occupancy data from a real office building to evaluate the performance of an agent-based occupancy simulation model: the Occupancy Simulator. The occupancy patterns of various occupant types were first derived from the measured occupant schedule data using statistical analysis. Then the performance of the simulation model was evaluated and verified based on (1) whether the distribution of observed occupancy behavior patterns follows the theoretical ones included in the Occupancy Simulator, and (2) whether the simulator can reproduce a variety of occupancy patterns accurately. Results demonstrated the feasibility of applying the Occupancy Simulator to simulate a range of occupancy presence and movement behaviors for regular types of occupants in office buildings, and to generate stochastic occupant schedules at the room and individual occupant levels for building performance simulation. For future work, model validation is recommended, which includes collecting and using detailed interval occupancy data of all spaces in an office building to validate the simulated occupant schedules from the Occupancy Simulator.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Adsorption-based direct air capture using hierarchical porous composites prepared via confined-space crystallization

Capturing CO₂ at trace concentration remains a critical challenge in sustainable carbon management via adsorption, as conventional adsorbents suffer from low CO₂ selectivity, poor moisture tolerance, and energy-intensive regeneration requirements. Here, we report a hierarchical Ba²⁺-exchanged silicoaluminophosphate (Ba²⁺-CSAPO-34) composite synthesized via confined-space crystallization within an activated carbon matrix. Comprehensive characterization revealed a confined nucleation mechanism and the successful incorporation of Ba²⁺ active sites within the SAPO-34 framework, achieved via a two-step liquid ion-exchange protocol. The core-shell architecture combines the selective CO₂ binding of Ba²⁺-functionalized SAPO-34 with the hydrophobic protection of the carbon shell. Fixed-bed adsorption tests demonstrated strong CO₂ binding (at 500-2500 ppm), no roll-up, and effective suppression of water affinity, while maintaining high selectivity even at 90% relative humidity. A phenomenological adsorption model, validated against dynamic breakthrough data, accurately predicted dynamic adsorption behavior under real-world operating conditions, enabling rational process design for direct air capture (DAC) and closed-loop life support systems. Furthermore, these results establish Ba²⁺-CSAPO-34 as a scalable, moisture-resistant adsorbent that addresses key limitations in trace CO₂ capture, advancing practical implementation of carbon removal technologies.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

A mesoscale 3D model of irradiated concrete informed via a 2.5 U-Net semantic segmentation

The concrete biological shield in light-water reactors is exposed to neutron and gamma irradiation, which deteriorates the concrete’s mechanical properties in the long term. To assess the irradiation-induced damage, predictive mechanical models are developed and used in parallel with the characterization of irradiated concrete samples. Realistic 3D simulation domains can drastically improve a model’s prediction. In this work, we utilized x-ray computed tomography (XCT) data of a concrete specimen to reconstruct its 3D microstructure. The XCT data shows low contrast between the concrete’s aggregates and cement paste, resulting in poor image segmentation when using traditional unsupervised techniques. To address this issue, we developed and trained a 2.5D U-Net model on only 24 pre-labeled XCT layers to segment 651 layers of the XCT data. The overall F1-score of the model is approximately 96%. Then, we created a 3D finite element (FE) mesh based on the stack of segmented images. The FE model contains radiation-induced expansion, damage, and creep. The constitutive equations are adapted to each phase (aggregates and cement paste). Here, we simulated the effects of neutron irradiation in the concrete specimen as well as the specimen’s mechanical response to uniaxial compression. Finally, model validation was performed using experimental data on similar concrete specimens in the literature.

2.5D U-Net↗
DOE OSTI2019

Comments on “Comparison of energy consumption in desalination by capacitive deionization and reverse osmosis”

Capacitive deionization (CDI) is an emerging brackish water desalination technology in which ions are removed from water by electrostatically adsorbing them onto porous electrodes. Recently, Qin et al. presented an estimate of energy consumption for CDI schemes, and compared the energy consumption of CDI to the energy consumption of a particular reverse osmosis operation scheme which they propose. Qin et al. estimate very high values of energy consumption in CDI for brackish water desalination (e.g. ~1 to 2 g/L salt solution), and these values and trends do not agree with published experiments for CDI or with experimentally validated models for CDI. The current comment identifies important scaling errors and incorrect values in their model resistance parameters, and then discusses unphysical trends predicted by their model. We do not attempt provide a comprehensive review of their model, operation, estimates, and figures, but rather concentrate on several key issues. We present our comments in two sections dealing with resistances and energy metrics, respectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Evaluation of hybrid evaporative-vapor compression air conditioners for different global climates

Currently, a majority of global residential air-conditioning requirements are met using cooling systems based on the vapor compression cycle (VCC). To meet the future demand for space cooling and to reduce the corresponding environmental impact, there is a need for alternative cooling systems which require less resources and exhibit a higher coefficient of performance (COP). One of proposed alternatives is called the hybrid evaporative-vapor compression (HEVC) cycle, which utilizes adiabatic latent cooling in combination with the VCC. In this paper, we conducted a feasibility analysis of a HEVC system by comparing its performance to that of VCC for various global climates. To accomplish this, we developed and validated models to simulate the performance of residential VCC and HEVC systems. ASHRAE weather data and design conditions were then used to compare the performance of the two systems. In general, HEVC systems are best suited for hot arid climates with energy reduction greater than 20%. Conversely, humid climates are not suitable for HEVC adoption due to degraded performance of evaporative coolers in these climates. In addition to comparing the energy savings from HEVC systems, it is also critical to analyze their water consumption. Generally, climates that benefit the most from HEVC technology tend to also experience water scarcity issues. Thus, both the energy savings and water consumption of HEVC systems must be analyzed to guide the discussion on their adoption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

A direct contact cooler design for simultaneously recovering latent heat and capturing SO x and NO x from pressurized flue gas

Integrated SO x and NO x removal technology using a direct contact cooler is a promising alternative for cleaning coal combustion flue gas, especially for pressurized combustion systems. Past investigations of integrated SO x and NO x removal have been limited to low-temperature processes, where the flue gas has been cooled upstream of the removal unit, and the moisture in the flue gas has been condensed out. Here this work presents a novel design that recovers the flue gas heat while simultaneously removing SO x and NO x in a single reactive-absorption column – direct contact cooler. A validated model was used to evaluate different direct contact cooler designs. Modeling results suggested that a counter-current column with a single water inlet can scrub 83% of the NO x and 96.5% of the SO x in 115 s, while an optimized design with multiple water inlets enhances the scrubbing of NO x by 9 percentage points and SO x by 3.5 percentage points, due to a 34% increase in residence time. It is also observed that the liquid-phase reaction between absorbed SO x and NO x plays a significant role in the removal of SO 2 from the flue gas for high-temperature scrubbing compared with low-temperature scrubbing. The design reinforces the potential of high-temperature SO x -NO x removal and heat recovery and suggests a means of reducing capital costs for such columns.

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

Air compressor load forecasting using artificial neural network

Air compressor systems are responsible for approximately 10% of the electricity consumed in United States and European Union industry. As many researches have proven the effectiveness of using Artificial Neural Network inair compressor performance prediction, there is still a need to forecast the air compressor electrical load profile. The objective of this study is to predict compressed air systems’ electrical load profile, which is valuable to industry practitioners as well as software providers in developing better practice and tools for load managementand look-ahead scheduling programs. Two artificial neural networks, Two-Layer Feed-Forward Neural Networkand Long Short-Term Memory were used to predict an air compressors electrical load. Compressors with three different control mechanisms are evaluated with a total number of 11,874 observations. Here, the forecasts were validated using out-of-sample datasets with 5-fold cross-validation. Models produced average coefficient ofdetermination values from 0.24 to 0.94, average root-mean-square errors from 0.05 kW - 5.83 kW, and meanabsolute scaled errors from 0.20 to 1.33. The results indicate that both artificial neural networks yield goodresults for compressors using variable speed drive (average R 2 = 0.8 and no naïve forecasting), only the longshort-term memory model gives acceptable results for compressors using on/off control (average R 2 = 0.82 and no naïve forecasting), and no satisfactory results are obtained for load/unload type air compressors (models constituting active forecasting).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Modeling forest site productivity using mapped geospatial attributes within a South Carolina Landscape, USA

Spatially explicit mapping of forest productivity is important to assess many forest management alternatives. We assessed the relationship between mapped variables and site index of forests ranging from southern pine plantations to natural hardwoods on a 74,000-ha landscape in South Carolina, USA. Mapped features used in the analysis were soil association, land use condition in 1951, depth to groundwater, slope and aspect. Basal area, species composition, age and height were the tree variables measured. Linear modelling identified that plot basal area, depth to groundwater, soils association and the interactions between depth to groundwater and forest group, and between land use in 1951 and forest group were related to site index (SI) (R 2 =0.37), but this model had regression attenuation. We then used structural equation modeling to incorporate error-in-measurement corrections for basal area and groundwater to remove bias in the model. We validated this model using 89 independent observations and found the 95% confidence intervals for the slope and intercept of an observed vs. predicted site index error-corrected regression included zero and one, respectively, indicating a good fit. With error in measurement incorporated, only basal area, soil association, and the interaction between forest groups and land use were important predictors (R2 =0.57). Thus, we were able to develop an unbiased model of SI that could be applied to create a spatially explicit map based primarily on soils as modified by past (land use and forest type) and recent forest management (basal area).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Numerical analysis of soot emissions from gasoline-ethanol and gasoline-butanol blends under gasoline compression ignition conditions

In the present work, computational fluid dynamics (CFD) simulations of a single-cylinder gasoline compression ignition (GCI) engine were performed to investigate the impact of blending two biofuels, ethanol and n-butanol, with gasoline on the trade-off between combustion phasing and soot emissions under low load conditions. Here, in order to represent market gasoline (RD5-87), a four-component toluene primary reference fuel (TPRF) + ethanol (ETPRF) surrogate (with 20% ethanol by mole; E20) was formulated using a neural network based octane predictor such that the surrogate had the same ethanol content, Research Octane Number (RON) and Octane Sensitivity (S). In addition, a novel skeletal kinetic mechanism for ETPRF and TPRF + n-butanol (BTPRF) blends, incorporating polycyclic aromatic hydrocarbon (PAH) chemistry, was developed. A three-dimensional (3D) engine CFD formulation employing the skeletal mechanism, adaptive mesh refinement (AMR), finite-rate chemistry approach, and hybrid method of moments (HMOM) was adopted to capture the in-cylinder combustion phenomena and soot emissions. The engine CFD model was validated against RD5-87 experimental data for a broad range of start-of-injection (SOI) timings (-21/-27/-36/-45 crank angle degrees (CAD) after top-dead center (aTDC)), with respect to in-cylinder pressure, heat release rate, combustion phasing, and soot emissions. The closed-cycle simulation results were analyzed to elucidate the non-monotonic trend of soot emissions versus SOI timing: SOI-36 > SOI-45 > SOI-21 > SOI-27. Thereafter, the validated CFD model was employed to simulate the combustion of a gasoline-ethanol blend with 45% (by mole) ethanol (E45) and a gasoline-butanol blend with 45% (by mole) n-butanol (B45) under the same operating conditions to study the effects of fuel composition and SOI timing on combustion phasing and soot emissions. The sooting propensity followed the trend: B45 > E20 > E45 at all SOI timings. Overall, it was observed that the autoignition propensity was primarily related to fuel chemistry. On the other hand, sooting propensity showed strong coupling with both fuel chemistry and physical properties, with greater impact of fuel physical properties at advanced SOI timings.

30 DIRECT ENERGY CONVERSION↗