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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Recovery of Natural Gas Equipment Emissions into Gas Compression Engines for the Reduction of Potential Greenhouse Gas Emissions

Since the turn of the millennium, the United States (U.S.) oil and natural gas (ONG) industry has nearly doubled its natural gas production rate. As a result, the ONG industry has recently come under increasing scrutiny for its contributions to greenhouse gas (GHG) emissions. Consequently, various solutions to this problem have been proposed and formulated to reduce the impacts of GHG emissions on the environment. West Virginia University (WVU) have found it important to research the impacts of recovering vented gas streams into prime-mover engines. The U.S. Department of Energy (DOE) and National Energy Technology Laboratory (NETL) have granted WVU funding to research and develop a “Methane Mitigator” (M2) - a “Scalable Vent Mitigation Strategy to Simultaneously Reduce Methane Emissions and Fuel Consumption from the Compression Industry.” One of the main areas of interest for this research was the collection of emissions from natural gas equipment into a Caterpillar G3508J natural gas compression engine. The parameters being analyzed from the engine were brake-specific emissions and power output. The emissions sources considered for this research were pneumatic controllers (PCs), reciprocating compressor vents, and the engine’s open crankcase breather. The compressor vent and PC emissions were simulated using a mass flow controller (MFC) and flowed into the engine using two separate methods: (1) directly into the air intake, and (2) through a retrofitted closed crankcase ventilation system (CCV), serving as a buffer volume. The crankcase emissions were quantified without the CCV, and the impact on exhaust emissions from circulating the crankcase gases into the intake was measured. The simulated compressor vent and PC flows from the MFC had limited effect on the steady state operation of the engine and resulting performance. When the simulated flows were fed directly into the engine’s air intake, the changes within the engine’s continuous performance and emission parameters were larger but lasted for shorter durations. Conversely, when the simulated flows were fed into the CCV before entering the air intake, the changes in the engine’s performance and emission parameters were less pronounced for continuous analysis but lasted for longer durations. In either case, the continuous emission changes in both emissions and performance varied in size depending on the test scenario being run, but the cycle average changes in emissions and performance showed little impact overall compared to the engine’s baseline operation. As a result, the inclusion of a CCV shows a decrease in baseline carbon dioxide equivalent (CO2-eq.) engine emissions (from combined exhaust and open crankcase) of almost 4%. Likewise, the CCV inclusion reduced baseline total methane (CH4) from combined exhaust and open crankcase by upwards of 16%. These atmospheric emissions only decreased further with the inclusions of collected PC and compressor vent flows. The resulting changes in time-averaged rated exhaust behavior (or lack thereof) prove that the proposed M2 system could likely be deployed at sites with modern lean-burn natural gas engines as a viable option for reducing and eliminating potential GHG sources that would have otherwise been unutilized as energy sources.

03 NATURAL GAS↗
DOE OSTI2025

Python Library for Monte Carlo Simulations with Ab Initio and Machine-Learned Interatomic Potentials

There is a growing need in the simulation community for software that provides a transparent, reproducible, usable, and extensible (TRUE) Monte Carlo (MC) simulation framework employing energies from ab initio methods and machine-learning interatomic potentials (MLIPs). We introduce a Python library (ASE-MC) that adds Monte Carlo functionality to the Atomic Simulation Environment (ASE) package. Now, we can combine the powerful tools used to build systems and perform ab initio and MLIP in ASE with MC simulation algorithms to sample the configurational space with a concise Python script. After presenting the design philosophy, we demonstrate the flexibility of our approach using selected examples. These example simulations include liquid water described with a message-passing MLIP in the canonical and isothermal–isobaric ensembles, sampling the characteristic dihedral angle of biphenyl and comparing an MLIP to first-principles calculations, and a grand canonical Monte Carlo simulation of ammonia adsorption on Pt(111). These examples showcase the main features of the software, which include flexibility in the choice of ab initio or MLIP engine, ab initio or MLIP grand canonical MC with cavity bias insertions and deletions, the ability to add custom MC moves to the move set, and how users can condense complex MC workflows into a single Python script. Finally, this library serves as a framework for reproducible Monte Carlo simulations, facilitating easy reproduction of the work and application to new systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Ground-motions site and event specificity: Insights from assessing a suite of simulated ground motions in the San Francisco Bay Area

This article presents the results of a research that is part of a larger collaborative effort between the Lawrence Berkeley National Laboratory and the Pacific Earthquake Engineering Research Center, funded by the US Department of Energy Office of Cybersecurity, Energy Security and Emergency Response. The main objective of this study is to assess a suite of near and far-field simulated ground motions obtained from 20 realizations of an M7 Hayward Fault earthquake in the San Francisco Bay Area, California USA, and inform the selection of rupture simulation parameters leading to strong motions. To this aim, comparisons are conducted with NGA-W2 and directivity ground-motion models and a selected population of records. An archetypal steel moment-resisting frame is utilized to assess infrastructure response distributions. The analyses carried out for each simulated event and subdomain with consistent properties in terms of shallow shear-wave velocity proved to be instrumental for better interpreting the differences between simulated motions and empirical models. The main reasons identified for variances between simulations and empirical relationships included (1) directivity effects fully captured by the simulations across the full breadth of rupture models; (2) site vicinity to ruptures that incorporate large-slip patches, particularly if these are in the forward-directivity direction; and (3) presence of geologic structures that can “trap” seismic waves and produce ground motions with large amplitude and long signal duration. The analyses carried out in this work provide a path for interpreting ground-motion site and event specificity obtained from a suite of physics-based simulations, differing only in the rupture model characterization, to inform the selection of simulation scenarios for site-specific engineering analyses under strong excitations. Evidence from this work points to the possibility that current hazard models may underestimate ground-motion intensities in areas where the combined effect of directivity and site conditions results in large ground-motion amplitudes.

58 GEOSCIENCES↗
DOE OSTI2025

Main Shaft Bending Moment Analysis for a Gamesa G97 2-MW Wind Turbine

In a collaborative project between Siemens Gamesa Renewable Energy and the National Renewable Energy Laboratory (NREL), a cost-effective method to measure dynamic main shaft torque and the influence of non-torque loads was applied to the gearbox of the Gamesa G97 2-megawatt (MW) wind turbine at the NREL Flatirons Campus and verified through a field test campaign that took place in 2023. The method involved the installation of fiber-optic sensors on the ring gear of the gearbox. Additionally, traditional strain gauges and a rotary encoder were installed on the main shaft to measure mechanical torque and orthogonal bending moments. We compare the measured total main shaft bending moments from the field test campaign to those predicted by an updated OpenFAST model of the G97 wind turbine for similar environmental conditions. We also assessed the sensitivity of the predicted bending moment to varying levels of turbulence intensity, shear exponent, and yaw error.

17 WIND ENERGY↗
DOE OSTI2026

Towards Commercialization of Low-Cost, Crack-Tolerant, Screen-Printable Metallization by Full-Size Module Testing and Field Characterization

This project is motivated by the need to develop a materials engineering solution to reduce solar module degradation caused by cell cracks. The cell-crack-induced power loss is a long-term degradation mechanism and one of the main causes of solar panel field failures. Cell cracks can occur during module fabrication, transportation, installation, and long-term operation due to thermomechanical stressors. Our team’s internal estimation – based on the national weather pattern, frequency of severe weather, and 39- GW asset survey by Heliolytics – reveals that the cell-crack-induced module degradation translates to lost revenues >$17B over an average 5-year period for solar farm owners and to reduced reliability (<25 years panel lifetime) for solar energy consumers. In response to this challenge, the prime recipient offers a metal matrix composite (MMC) silver paste that is tailor-engineered for screen-printing gridlines and busbars, which serve as the electrical contacts on solar cells. We formulate our MMC paste by adding low-cost (∼0.02¢/WDC for research grade), surface-engineered carbon nanotubes to commercially available silver paste. The MMC paste offers a drop-in, cost-effective solution to cell cracks for solar cell and module manufacturers. The main goal of this project was to conduct field-relevant, module-level analysis and qualification of MMC metallization.

14 SOLAR ENERGY↗
DOE OSTI2024

Mitigation for Removal of Building 01-202681 in the Main Storage Yard of the Area 1 Subdock, Nevada National Security Site, Nye County, Nevada

The Main Storage Yard was originally recorded as SHPO Resource No. S2772 in 2020 during an architectural survey of the Area 1 Subdock (Collins et al. 2022). It was recommended individually eligible for listing in the NRHP under Criteria A and C and as contributing to the significance of the potential Area 1 Subdock Historic District. The SHPO concurred with these determinations in a letter dated April 29, 2022 (Reed). The Main Storage Yard retains all seven aspects of integrity. The location, design, materials, workmanship, feeling, and association have not changed since the original construction. Since the purpose of the yard is to maintain storage equipment that is actively being used, the design and feeling will change each time equipment is moved. Such actions reinforce the integrity of design and feeling. Buildings 01-101 and 01-102 were removed (Collins and Menocal 2020), but the other buildings and storage yard remain. Therefore, the setting has been changed, but not to the degree that the Main Storage Yard no longer conveys its significance (see Figures 4 and 5 for comparison). The Main Storage Yard was designed to facilitate the relocation of the Area 3 Subdock to Area 1 in 1985. The design for the overall Subdock provided a centralized cluster of buildings surrounded by two large storage yards. While the North Storage Yard largely serves as overflow storage, the Main Storage Yard holds the majority of drill rigs and drilling equipment needed to support big hole drilling. The Main Storage Yard and its contents were essential elements of the nuclear testing drilling program on the NNSS thus making it eligible for the NRHP under Criterion A for its contribution to broad patterns of history by storing specially designed equipment for underground nuclear testing at the NNSS. It is also eligible under Criterion C as it is an engineered landscape that now serves as an open-air repository of drilling technology and nuclear testing. In addition to its individual significance, the Main Storage Yard also contributes to the significance of the Area 1 Subdock Historic District as it showcases a variety of big-hole drilling equipment, support facilities, and warehouses that were specially designed for nuclear testing at the NNSS. Despite the demolition of two contributing elements to date, the district still contains numerous examples of other facilities with the purpose of supporting big-hole drilling; therefore, the district still remains eligible under Criteria A and C.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Thermal Damage Potential of Electric Vehicles

The main objective is to assess the risk that electric vehicle (EV) battery fires pose regarding thermal damage to other vehicles involved in a crash and to compare EV and internal combustion engine vehicle (ICEV) fires. A literature review of experimental data and statistics are used to perform the assessment. The findings indicate: (1) the heat flux emitted from an EV and ICEV fire are similar due to cabin materials being the main contributor to heat flux, (2) for ICEVs involved in a crash with fuel tank leakage, the thermal damage is significantly more than from an EV fire for equivalent fire durations, (3) the thermal damage potential from ICEV pool fires is at least 5 times higher than EV fires, and (4) EV and ICEV crashes resulting in a fire is about 0.002% and 0.2%, respectively. Thus, EV battery fires have a lower risk than ICEV fires.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Computational analysis of flame initiation, quenching, and re-ignition in a prechamber natural gas engine under varying EGR-dilution levels

The on-road natural-gas (NG) fueled transportation relies on stoichiometric spark-ignition engines for the advantages of simple after-treatment system despite the efficiency penalty relative to lean-burn combustion strategies. Exhaust gas recirculation (EGR) has the potential to reduce this efficiency gap at low to moderate loads without the need for complex lean-exhaust aftertreatment systems. However, EGR dilution leads to reduced combustion stability and increased cycle-to-cycle variability. A promising technology that has the potential to achieve reliable operation under diluted conditions is the prechamber ignition (or turbulent jet ignition) which uses chemically active turbulent jets generated from combustion inside a prechamber to initiate, stabilize and accelerate combustion of the mixture inside the main chamber. The present work focusses on developing a RANS-based CFD approach to accurately reproduce in-cylinder phenomena in a stoichiometric NG prechamber-assisted heavy-duty engine without relying on complex combustion models that account for turbulence-chemistry interactions. This is necessary because reactive prechamber jets at high EGR dilution tend to extinguish while emerging into the main chamber, which is followed by a phase of re-ignition — a phenomenon that conventional G-equation or well-stirred reactor combustion models cannot reproduce. With addition of a damping multiplier to the well-stirred reactor model, the predictions are seen to show good agreement with experimental pressure evolution and combustion images acquired from a single cylinder Cummins N-14 optical diesel engine retrofitted with a prechamber ignition system. Model predictions of local heat release in the flame and temperature evolution inside the flame are used to investigate combustion dynamics in the prechamber and the main chamber. It is seen that the well-stirred reactor model with the inclusion of damping is able to reproduce the temporary reduction in heat release within the flame, which can be considered equivalent to quenching of jets, and the subsequent re-ignition of the flame inside the main chamber. The delay between quenching and re-ignition depends on the amount of dilution, as explained by an illustration of flame evolution in a Borghi diagram.

Prechamber ignition↗
DOE OSTI2025

Design, Optimization, and Control of Floating Offshore Wind Farms for Optimal Energy Production (Final report)

The uncertainty and irregularity of ocean waves and the ocean environment is a major factor in the development of commercial scale floating wind turbines as the operation of floating structures in such an environment can lead to irregular and unpredictable loading, fatigue, and ultimately a reduction in the operational life of the turbine system which affects energy production over the lifetime of the turbine. Control solutions that can limit float motions and mitigate stressful events on the structure become essential for extending lifetime and limiting the operational uncertainty of a floating wind turbine. Digital twins are computational replicas of physical systems that operate in parallel with the operation of the physical system. Given advanced knowledge of a systems input, digital twins have the ability to predict the behavior of a system in advance, which can be valuable in the control of that system. In this project, we developed and assessed potential digital twin models developed in house and openly available (OpenFast) for use in the real time control of the six degree of freedom response motions of a floating wind turbine in ocean waves. Coupling these models with near-field real time irregular sea surface (wve) measurement/sensings and prediction models, we used the digital twin to predict how the floating turbine will respond to the incoming waves. Applying this information to a motion control system of the float, one can limit and control float motions to prevent undesirable loading events/large angular motions, thus increasing system life and ultimately contributing to optimizing energy production. Due to the computational intensity of operating a digital twin in real time, we investigated the use of artificial intelligence techniques to speed-up the processes of the digital twin, as well as the wave reconstruction/prediction models. Model tank testing at the University of Rhode Island and University of Maine both validated and demonstrated the developed techniques on simple float geometries and a scale model of the NREL 15 MW reference turbine.

17 WIND ENERGY↗
DOE OSTI2025

EIC ESR beam position monitors thermal and thermomechanical study preliminary design

The Electron Ion Collider (EIC) Electron Storage Ring (ESR) Beam Position Monitors (BPM) are designed to monitor the electron beam orbit position on a turn-by-turn and bunch-by-bunch basis in the vacuum chamber. Large variations in ESR fill pattern and bunch intensity imposes a large dynamic range on the BPM system design. And given the large ESR beam current - up to 2.5 A with 1160 x 20 nC bunches – the heating by synchrotron radiation (SR) and beam impedance is a significant concern. The high energy of the electrons – up to 18 GeV – leads to scat tering of the SR that produces high radiation doses and as sociated heating of structures away from the SR impact area. Because of this intense heating, and stringent position stability requirements, an in-depth engineering analysis was carried out. This paper will review the analysis made of the preliminary design and its main outcomes.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Precision Structure Engineering of High-Entropy Oxides under Ambient Conditions

High-entropy oxides (HEOs) have unveiled a unique frontier in the realm of heterogeneous catalysis, taking advantage of the entropic effect and increased complexities to deliver ultrahigh stability and large tuning capability. However, current HEO synthesis mainly relies on high-temperature annealing approaches affording HEOs possessing no or low surface area, inferior active site exposure efficiency, and low controllability over the structure tuning. The grand challenge lies in producing high-quality HEO catalysts with high active site utilization efficiency, which relies on precision structure engineering, preferably under mild conditions. In this work, an in situ lattice engineering approach was developed to afford a supported HEO catalyst under ambient conditions. The HEO compositions (CuCoFeNiMnO x ) were uniformly integrated into the lattice of CeO 2 driven by cavitation-induced nucleation being generated via ultrasonication. The as-afforded catalysts were featured by high surface area, atomically dispersed HEO compositions, active redox properties, abundant oxygen vacancies (O V ), antiagglomeration, and high phase stability under harsh conditions. Compared with the ex situ introduction of HEO on the surface, the in situ method provides dual benefits to maintain the dispersity of HEO via entropic and lattice confinement effects. Engineering the complex HEO within the lattice of fluorite-structured CeO 2 also yields abundant defects (e.g., O V ) and active metal sites with strong reducing properties (e.g., Ce 3+ and Cu + ), which greatly improves the activity of the lattice oxygen and tunability of the adsorption behavior of the guest molecules, especially in the presence of impurities (e.g., water and propane). The catalytic performance of the supported HEO catalyst in oxidative procedures surpasses the pure dense phase HEO as well as the ex situ-generated catalysts. Further, the synthesis approach being developed in this work, together with the fundamental understanding in structure evolution and reaction mechanism, showcases a facile pathway under ambient conditions to generate stable catalysts capable of maintaining structural robustness in high-temperature conditions while delivering enhanced catalytic performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Performance evaluation of automated data-driven feature extraction and selection methods for practical and scalable building energy consumption prediction models

Here, this study quantifies the impact of automated feature engineering methods (feature extraction and selection) on the quality and accuracy of machine learning models that predict building energy consumption. The case study compares model performance for three main scenarios: baseline (no feature extraction and selection), feature extraction only, and feature extraction combined with feature selection (filter and/or wrapper methods) for fully trained machine learning models for 200 metered/sub-metered energy measurements across 118 real buildings. For consistency, the same machine learning model architecture (a black box deep learning neural network with probabilistic forecast output) was used for all scenarios. Based on results, all feature engineering methods provided noticeable prediction accuracy improvements (e.g., 29%-68% median prediction improvement) compared to baseline scenarios. However, in this application, feature selection methods provide little practical value due to their limited performance gains and high computational cost. Smarter algorithm development supported by better computational environments will be needed before feature selection methods can reliably and efficiently improve predictive model performance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Review of Reactor Facilities without Main Control Rooms

Small, advanced reactors may require few, if any, safety-related human actions (HAs) and fewer HAs to monitor and control the plant. In comparison to large light water reactors, these are significant changes that have implications for many aspects of an applicant's human factors engineering (HFE), including control room design, plant staffing, and the management of safety functions. To support the Nuclear Regulatory Commission's (NRC) ability to evaluate these changes, information needs to be developed addressing the characteristics and potential issues. The objectives of our research were to (1) identify when a traditional main control room (MCR) may not be necessary, (2) identify workplace design alternatives to traditional MCRs, and (3) develop guidance for reviewing an applicant's workplace designs with and without a MCR. We determined that the safety question isn't so much justifying why a design has no MCR, but rather verifying that important human actions can be accurately and reliably performed under a range of challenging conditions using the HSIs provided regardless of their location. We developed guidance to review alternatives to MCRs based on HFE analyses for determining workplace location and design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Novel data interpretation method for DIII-D divertor retarding field energy analyzer with 3-D particle-in-cell simulations

A novel data interpretation process that utilizes comprehensive particle-in-cell (PIC) simulations is developed for the new retarding field energy analyzer (RFEA) currently being constructed at DIII-D for the lower divertor using the Divertor Material Evaluation System. Furthermore, this probe is expected to survive a heat load of up to 100 MW/m 2 for up to 5 s and reliably measure the main ion temperature (T i ) on the divertor target ranging from 10 to 200 eV. These extreme conditions posed significant engineering limitations on the probe geometry, thus extensive validation work has been performed. The conventional fitting method for the RFEA I–V characteristics is based on a simplified 1-D model without considering the ion space charge inside the probe cavity and may not be sufficient for probes designed for the DIII-D divertor environment. In this article, a more realistic description of the particle propagation process within the RFEA cavity is achieved by including both 3-D geometric effects and ion space charge in the PIC simulations, and the capability to reconstruct the ion energy distribution functions is demonstrated with reasonable consistency.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

FORCE Update 2024

The Framework for Optimization of Resources and Economics (FORCE) tool suite is the U.S. Department of Energy’s Nuclear Integrated Energy Systems (IES) Program flagship tool suite for technoeconomic IES analysis of IES. This tool suite is useful for analysis designed to evaluate and improve the technoeconomics of energy production systems, particularly for systems including nuclear technology. In this report, we document the development activity for the FORCE tool suite to extend its capabilities as performed during fiscal year 2024. In addition to reliability and accessibility, capability is one of the three standards guiding the development of the FORCE tool suite and the software codes that are its constituent parts. Extending the capabilities of the FORCE tool suite allows analysis both within the IES program as well as industry, university, and laboratory partners to perform analysis with more accuracy, insight, and impactful narrative. Four areas of capability development were the focus of activity this year: economic parameter uncertainty quantification, multiresolution analysis, components-to-optimization workflow automation, and statespace construction workflows for real-time optimal control. In economic parameter uncertainty quantification, the ability of HERON to capture risk due to scenarios (weather and energy demand uncertainty) was expanded to also include uncertainties in financial parameters such as capital cost or operation and maintenance costs. By including these sources of uncertainty, which are sometimes very large compared with scenario uncertainty, HERON is better able to capture the risk posed by investment in various IES technology. Because of this, analysts can also consider the reduction in risks that can be realized by choice of some technologies. In multiresolution analysis, development activity extended on work completed previously. In fiscal year 2023, methods for decomposing time series signals, such as demand, solar and wind availability, and price profiles, were analyzed and down-selected to those most effective at splitting signals into different resolutions. These resolutions allow considering the influence of different energy demand and supply behaviors across different time scales. For example, energy demand might be divided into seasonal, weekly, and hourly profiles. In fiscal year 2024, this preliminary work was extended and implemented within the Risk Analysis Virtual Environment (RAVEN) risk and uncertainty analysis platform, which is used throughout the FORCE framework. This development of the “multi-resolution time series analysis” (MR-TSA) module in RAVEN allows training synthetic history generators on complex time series. These synthetic history generators can then be used in HERON for generating scenarios that represent possible market and weather scenarios that can be analyzed on different time scales. We envision completing this work in the future, implementing multiresolution dispatch optimization strategies that can make the most beneficial use of these stratified time histories. In components-to-optimization workflow development, workflows for translating user inputs of components into algorithms for algebraic optimization were selected and implemented. Similar algorithms within the Holistic Energy Resource Optimization Network (HERON) were separated from the main code base of HERON and gathered with the components-to-optimization workflows in the new Dispatch Optimization Variable Engine (DOVE) software library. This modularization allows FORCE users to analyze dispatch optimization and energy system duty cycles independently of HERON, which previously was a burdensome task. Additionally, these dispatch optimization algorithms, set up in an independent library, can now be used across all software applications within FORCE, especially including the real-time optimal control software Optimization of Real-time Capacity Allocation (ORCA). Allowing FORCE software to share dispatch optimization algorithms within a single library allows for improved software maintenance and reliability. In statespace characterization workflow development, alternative workflows for optimizing dispatch with additional technical accuracy was the focus, particularly to improve the real-time optimization decision making in ORCA. Using algorithms and workflows initially developed for the Feasible Actuator Range Modifier (FARM), workflows for determining the statespace representation of IES were identified and demonstrated. The resulting dispatch optimization required a more robust optimization algorithm than that originally used in HERON (and moved to DOVE), which required adding an alternate workflow to DOVE that can more accurately match the behavior of physical systems using a partial differential equation representation. In conclusion, capability developments in the FORCE tool suite in fiscal year 2024 have improved the ability of the FORCE tool suite to perform

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Simultaneous Reduction of NOx and Fuel Consumption for Off-Road Powertrains

Simultaneously reducing criteria pollutants and fuel consumption is important for clean air and improving vehicle total cost of ownership. The goal of this effort was focused on a 90% NOx reduction and 10% fuel savings for an off-road 407 kW diesel engine. The baseline was a production Fiat Powertrain 13L engine and aftertreatment system meeting 0.4 g/kW-hr NOx. The baseline system was quantified over the NRTC, RMC, new low load cycle and five field cycles. A next generation engine was built incorporating several fuel-efficient design features, including a higher compression ratio, increased fuel-rail pressure, low-friction piston rings, and a high-efficiency variable-geometry turbocharger. Cylinder deactivation and EGR pump technologies were added to this engine as well. The combination was optimized prior to adding advanced aftertreatment systems, showing the trade-off of engine out NOx and exhaust temperature. Two next-generation catalyst technologies were employed into a LO-SCR plus main SCR system, both with and without an electric heater upstream of the LO-SCR. These catalysts were hydrothermally aged to simulate significant field use. Dual SCR dosing with newly developed controls played a critical role in achieving the proper split between the upstream LO-SCR and the downstream main SCR. Adding a next generation mixer for the downstream SCR proved essential in obtaining the final results. The optimal configuration required adding an electric heater to elevate the exhaust temperature at the LO-SCR for early cycle NOx reduction. The final results showed a 94.8% NOx reduction and 15.7% fuel savings on the composite NRTC.

McCarthy, James [Eaton Corporation]↗
DOE OSTI2025

Precursor Engineering of All-Inorganic Perovskite Absorber and Rapid Photonic Annealing for Large-Area Highly Stable Perovskite Solar Modules

Currently the all-inorganic perovskites were prepared by toxic dimethylformamide (DMF) as a main solvent, and small-area PSCs were prepared by a simple spin-coating method followed by lengthy thermal annealing. All these issues limited the commercialization of these PSCs. Therefore, it is necessary to develop an eco-friendly all-inorganic perovskite ink that can be coated over large areas at low temperatures followed by rapid annealing for the scale-up manufacturing with high compatibility to the industrial scale sheet-to-sheet or roll-to-roll processes.

14 SOLAR ENERGY↗
DOE OSTI2025

BOPTest As a Platform for Building Controls and Grid-Interactive Buildings Workforce Training

Building automation and controls are becoming increasingly complex with the emergence of Grid Integrated Efficient Buildings (GEBs) as well as new highly efficient sequences of operation and data-driven control schemes. However, there remains a significant gap in hands-on training opportunities for building operators and technicians to gain practical experience with advanced control systems in a low-risk environment. This paper presents BOPTEST (Building Optimization Performance Test) as a suitable platform for workforce training in building controls and GEB technologies. BOPTEST provides a suite of standardized building simulation test cases with a REST API, real-time control interfaces through BACnet, semantic models connecting users to building data, and built-in calculation of control metrics and performance indicators. The platform enables trainees to interact with virtual buildings using industry-standard protocols while learning how to implement and innovate control strategies. The training platform is designed to offer a structured and interactive learning experience for building engineers, helping them effectively develop, learn, and retain skills in fault identification, troubleshooting, and correction. The workflow is divided into three main phases: 1) Setup, 2) Exercise, and 3) Review, each comprising specific activities performed by either the instructor or the student. Initial pilot training sessions have yielded positive feedback from instructors and participants and demonstrates that BOPTEST effectively fills an industry need for a low-risk training resource via simulation of real building control systems, allowing trainees to gain practical experience before working in the field. The platform's ability to provide immediate performance feedback while maintaining familiar industry interfaces makes it particularly suitable for workforce development programs. This work provides a replicable model for leveraging building simulation in control education and training.

Paul, Lazlo↗