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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Low-Cost, Easy-To-Integrate and Reliable Grid Energy Storage System with 2 nd Life Lithium Batteries

Batteries retired from electric vehicles have the potential to extend their service as low-cost stationary energy storage systems. However, disperse battery state of health (SOH) and nonuniform battery characters often lead to compromised battery performance and reliability, which greatly hinder their adoption. A Heterogenous Unifying Battery (HUB) system is proposed to stage 2 nd life battery bricks for a period, and enable them to attain improved SOH uniformity, performance, and reliability before being sold for 2 nd life applications, while simultaneously providing grid services. It may offer a technically and economically advantageous solution for the broad utilization of 2 nd use batteries. The goal of this project was to develop the hardware and software that enables the key functions of the HUB system. The first achievement of the project was the development of a 1kW scale proof-of-concept (POC) system, which comprises (i) a modular plug-n-play DC-DC power converter matrix with isolated series output connections to achieve fully independent control of energy flow to each of the connected battery units at low voltage; (ii) enhanced model based control that drives each batteries’ SOH towards uniformity while collectively providing grid energy storage services; and (iii) comprehensive procedures to perform battery diagnostics and prognostics. The second achievement was the development of a 100kW scale HUB system and demonstrated its performance of re-establishing battery SOH uniformity through a period of battery cycling operation. The final HUB system incorporates six DC-DC power converter matrices paired with six battery bricks. Hot swapping of a single battery brick while maintaining consistent system power was demonstrated and system operation was validated to be capable of implementing the approved grid duty cycle and of balancing and conditioning the battery bricks. Through the course of the project, the team optimized the building-block design, form-factors, and adjusted life balancing control. An up-sized 250kW Scale was developed and deployed in October 2022 with pack-level battery form factors, see photo in Figure 1 The third achievement of the project was to perform a techno-economic analysis in order to better understand the cost and revenue potentials in this new “recondition-then-resell" value proposition. The final TEA quantified the economics of new Li-ion batteries as well as second-life batteries processed via reconditioning and traditional binning. Results showed the reconditioned second-life batteries in this project to be economically favorable and viable in grid energy storage markets. The TEA results were published in the Applied Energy journal. The fourth achievement of the project was to deliver a tech-to-market plan for the HUB system that includes funding, IP, and manufacturing strategies. The final T2M plan outlines a business strategy in which the HUB provides a B2B service to EV companies as an alternative to battery recycling that can prepare batteries for 2nd life applications. A company named Smartville Inc. was founded to carry on the commercialization, funding, and technical IP licensing activities of the OPEN project.

25 ENERGY STORAGE↗
NASA NTRS2006

Satellite Estimates of Surface Short-wave Fluxes: Issues of Implementation

Surface solar radiation reaching the Earth's surface is the primary forcing function of the land surface energy and water cycle. Therefore, there is a need for information on this parameter, preferably, at global scale. Satellite based estimates are now available at accuracies that meet the demands of many scientific objectives. Selection of an approach to estimate such fluxes requires consideration of trade-offs between the use of multi-spectral observations of cloud optical properties that are more difficult to implement at large scales, and methods that are simplified but easier to implement. In this study, an evaluation of such trade-offs will be performed. The University of Maryland Surface Radiation Model (UMD/SRB) has been used to reprocess five years of GOES-8 satellite observations over the United States to ensure updated calibration and improved cloud detection over snow. The UMD/SRB model was subsequently modified to allow input of information on aerosol and cloud optical depth with information from independent satellite sources. Specifically, the cloud properties from the Atmospheric Radiation Measurement (ARM) Satellite Data Analysis Program (Minnis et al., 1995) are used to drive the modified version of the model to estimate surface short-wave fluxes over the Southern Great Plain ARM sites for a twelve month period. The auxiliary data needed as model inputs such as aerosol optical depth, spectral surface albedo, water vapor and total column ozone amount were kept the same for both versions of the model. The estimated shortwave fluxes are evaluated against ground observations at the ARM Central Facility and four satellite ARM sites. During summer, the estimated fluxes based on cloud properties derived from the multi-spectral approach were in better agreement with ground measurements than those derived from the UMD/SRB model. However, in winter, the fluxes derived with the UMD/SRB model were in better agreement with ground observations than those estimated from cloud properties provided by the ARM Satellite Data Analysis Program. During the transition periods, the results were comparable.

Wang, H.↗
DOE OSTI2020

Codisposal Waste Package Loading Options for DOE SNF and HLW PPT

The U.S. Department of Energy (DOE) is responsible for managing spent nuclear fuel (SNF) that is currently in, or will in the future come into, its possession. DOE must continue to safely store that SNF, transport it to an interim storage site or a repository, and dispose of it. These fuels come from a wide range of reactor types with various cladding materials and enrichments. Many of these reactors, now decommissioned, had unique design features, such as core configuration, fuel element and assembly geometry, moderator and coolant materials, operational characteristics, and neutron spatial and spectral properties, resulting in a large diversity of reactor and fuel designs. Because of the wide variety and conditions of SNF, a robust DOE Standard Canister was proposed that would confine radionuclides and preclude moderator. The DOE Standard Canister had four variations: 3.05-meter (10-foot) or 4.57-meter (15-foot) length, and 45.7-cm (18-inch) or 61.0-cm (24-inch) diameter. For ultimate disposal in the Yucca Mountain Repository, these canisters were to be grouped with 61.0-cm (24-inch) diameter high level waste (HLW) canisters in a 2.13-meter (84-inch) diameter co-disposal waste package. The smaller 45.7-cm (18-inch) diameter DOE Standard Canister could be placed in the middle of five HLW canisters. The larger 61.0-cm (24-inch) diameter DOE Standard Canister would take the place of one of the five HLW canisters on the outer ring in the co-disposal waste package. No DOE Standard Canisters have been loaded. A preliminary evaluation has estimated the number of elements of a fuel type that can fit into the different sizes of the DOE Standard Canister, but no definitive loading configuration has been selected. Changing the loading configuration could impact the number of loadable DOE Standard Canisters and the number of co-disposal waste packages needed for eventual disposition. This paper conveys the ranges of DOE Standard Canisters and HLW canisters that may be produced under certain conditions. It also examines the differences in the estimated number of co-disposal waste packages produced for eventual disposal when using different loading strategies in the DOE Standard Canister for Advanced Test Reactor (ATR), Peach Bottom, and High Flux Isotope Reactor (HFIR) SNF. Changing the loading configurations of ATR, Peach Bottom, and HFIR SNF slightly impacted the number of co-disposal waste packages that may be needed for ultimate disposal. The change in loading configuration was more impactful when a different canister was used, as opposed to varying the number of elements that could fit inside the same size canister. In one case, a reduction of co-disposal waste packages could be achieved by allowing mixing of short HLW canisters with long DOE Standard Canisters. The main conclusion from this analysis is that the ratio between HLW canisters and DOE Standard Canisters will drive the total number of co-disposal waste packages. If too many HLW canisters (i.e., more than five times the number of 18-inch DOE standard canisters) or DOE Standard Canisters are produced, some co-disposal waste packages may not have all positions filled. A co-disposal waste package may be filled with all HLW with no DOE Standard Canister, or a co-disposal waste package could be filled with a single DOE Standard Canister. A ratio that does not closely align to optimum could allow for the design of waste packages that hold just HLW canisters or just DOE SNF canisters.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Coral and Seawater Metagenomes Reveal Key Microbial Functions to Coral Health and Ecosystem Functioning Shaped at Reef Scale

The coral holobiont is comprised of a highly diverse microbial community that provides key services to corals such as protection against pathogens and nutrient cycling. The coral surface mucus layer (SML) microbiome is very sensitive to external changes, as it constitutes the direct interface between the coral host and the environment. Here, we investigate whether the bacterial taxonomic and functional profiles in the coral SML are shaped by the local reef zone and explore their role in coral health and ecosystem functioning. The analysis was conducted using metagenomes and metagenome-assembled genomes (MAGs) associated with the coral Pseudodiploria strigosa and the water column from two naturally distinct reef environments in Bermuda: inner patch reefs exposed to a fluctuating thermal regime and the more stable outer reefs. The microbial community structure in the coral SML varied according to the local environment, both at taxonomic and functional levels. The coral SML microbiome from inner reefs provides more gene functions that are involved in nutrient cycling (e.g., photosynthesis, phosphorus metabolism, sulfur assimilation) and those that are related to higher levels of microbial activity, competition, and stress response. In contrast, the coral SML microbiome from outer reefs contained genes indicative of a carbohydrate-rich mucus composition found in corals exposed to less stressful temperatures and showed high proportions of microbial gene functions that play a potential role in coral disease, such as degradation of lignin-derived compounds and sulfur oxidation. The fluctuating environment in the inner patch reefs of Bermuda could be driving a more beneficial coral SML microbiome, potentially increasing holobiont resilience to environmental changes and disease.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A direct numerical simulation study of the dilution tolerance of propane combustion under spark-ignition engine conditions

Modern spark ignition internal combustion (IC) engines rely on highly diluted fuel-air mixtures to achieve high brake thermal efficiencies. To support this, new engine designs have introduced high stroke-to-bore ratios and cylinder head designs that promote high tumble flow and turbulence intensities. However, mixture dilution through exhaust gas recirculation (EGR) is limited by combustion instabilities manifested in the form of cycle-to-cycle variability. Propane has been observed to have superior EGR dilution tolerance than gasoline, which makes it a very competitive low-carbon fuel for the new IC engines without sacrificing efficiency. Two-dimensional direct numerical simulations (DNS) are performed with detailed chemistry to study and contrast the effect of turbulence intensity and dilution on propane and iso-octane premixed flames at high pressure conditions similar to those in-cylinder. A new reduced mechanism for propane consisting of 53 transported species and 17 quasi-steady state species is developed based on a previously published mechanism and used in these simulations. Three levels of turbulence intensity and two levels of exhaust gas dilution are chosen based on conditions relevant to IC engine operation. The DNS results are analyzed based on the evolution of the flame surface area and the statistics of its driving terms, which are found to be similar for both fuels when there is no dilution but considerably different under high dilution. The analysis of the DNS data provides fundamental insights into the underlying mechanisms for improved stability under dilution.

42 ENGINEERING↗
DOE OSTI2021

Assessing the representation of the Australian carbon cycle in global vegetation models

Australia plays an important role in the global terrestrial carbon cycle on inter-annual timescales. While the Australian continent is included in global assessments of the carbon cycle such as the global carbon budget, the performance of dynamic global vegetation models (DGVMs) over Australia has rarely been evaluated. We assessed simulations of net biome production (NBP) and the carbon stored in vegetation between 1901 to 2018 from 13 DGVMs (TRENDY v8 ensemble). We focused our analysis on Australia's short-term (inter-annual) and long-term (decadal to centennial) terrestrial carbon dynamics. The TRENDY models simulated differing magnitudes of NBP on inter-annual timescales, and these differences resulted in significant differences in long-term vegetation carbon accumulation (–4.7 to 9.5 Pg C). We compared the TRENDY ensemble to several satellite-derived datasets and showed that the spread in the models' simulated carbon storage resulted from varying changes in carbon residence time rather than differences in net carbon uptake. Differences in simulated long-term accumulated NBP between models were mostly due to model responses to land-use change. The DGVMs also simulated different sensitivities to atmospheric carbon dioxide (CO 2 ) concentration, although notably, the models with nutrient cycles did not simulate the smallest NBP response to CO 2 . Our results suggest that a change in the climate forcing did not have a large impact on the carbon cycle on long timescales. However, the inter-annual variability in precipitation drives the year-to-year variability in NBP. We analysed the impact of key modes of climate variability, including the El Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD), on NBP. While the DGVMs agreed on sign of the response of NBP to El Niño and La Niña and to positive and negative IOD events, the magnitude of inter-annual variability in NBP differed strongly between models. In addition, we find that differences in the timing of simulated phenology and fire dynamics are associated with differences in simulated or prescribed vegetation cover and process representation. We further find model disagreement in simulated vegetation carbon, phenology, and apparent carbon residence time, indicating that the models have different types and coverage of vegetation across Australia (whether prescribed or emergent). Our study highlights the need to evaluate parameter assumptions and the key processes that drive vegetation dynamics, such as phenology, mortality, and fire, in an Australian context to reduce uncertainty across models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2011

NASA Risk Management Handbook

The purpose of this handbook is to provide guidance for implementing the Risk Management (RM) requirements of NASA Procedural Requirements (NPR) document NPR 8000.4A, Agency Risk Management Procedural Requirements [1], with a specific focus on programs and projects, and applying to each level of the NASA organizational hierarchy as requirements flow down. This handbook supports RM application within the NASA systems engineering process, and is a complement to the guidance contained in NASA/SP-2007-6105, NASA Systems Engineering Handbook [2]. Specifically, this handbook provides guidance that is applicable to the common technical processes of Technical Risk Management and Decision Analysis established by NPR 7123.1A, NASA Systems Engineering Process and Requirements [3]. These processes are part of the \Systems Engineering Engine. (Figure 1) that is used to drive the development of the system and associated work products to satisfy stakeholder expectations in all mission execution domains, including safety, technical, cost, and schedule. Like NPR 7123.1A, NPR 8000.4A is a discipline-oriented NPR that intersects with product-oriented NPRs such as NPR 7120.5D, NASA Space Flight Program and Project Management Requirements [4]; NPR 7120.7, NASA Information Technology and Institutional Infrastructure Program and Project Management Requirements [5]; and NPR 7120.8, NASA Research and Technology Program and Project Management Requirements [6]. In much the same way that the NASA Systems Engineering Handbook is intended to provide guidance on the implementation of NPR 7123.1A, this handbook is intended to provide guidance on the implementation of NPR 8000.4A. 1.2 Scope and Depth This handbook provides guidance for conducting RM in the context of NASA program and project life cycles, which produce derived requirements in accordance with existing systems engineering practices that flow down through the NASA organizational hierarchy. The guidance in this handbook is not meant to be prescriptive. Instead, it is meant to be general enough, and contain a sufficient diversity of examples, to enable the reader to adapt the methods as needed to the particular risk management issues that he or she faces. The handbook highlights major issues to consider when managing programs and projects in the presence of potentially significant uncertainty, so that the user is better able to recognize and avoid pitfalls that might otherwise be experienced.

Dezfuli, Homayoon↗
NASA NTRSDate not supplied

Developing Deep Learning Models for System Remaining Useful Life Predictions: Application to Aircraft Engines

Prognostics and health management (PHM) is an important part of ensuring reliable operations of complex safety- critical systems. System-level remaining useful life (RUL) estimation is a much more complex problem than making estimations at the component level, and system-level RUL methodologies remain sparse in the literature. Model-based approaches have traditionally worked in the past for components such as capacitors, MOSFETs, batteries, or hard-drives (to name a few examples), but developing high fidelity dynamics models of cyber physical systems that can be used to study the effects of multiple degrading components in the system remains a challenging task. Some initial work on model-based System RUL predictions was demonstrated in Khorasgani, et al [1], but, to generalize the system-level prognostics problem, we have to resort to pure data driven and hybrid approaches. In this work, we propose an end-to-end data- driven framework for developing deep learning models to predict remaining useful life of cyber physical systems operating under unknown faulty conditions. The raw data is organized with a data schema that improves the model development process and down stream data analysis tasks. Due to the unknown faulty conditions, the raw sensor data is transformed into signals that expose the underlying degradation processes, which are then used for model development. Bayesian Optimization is used to tune the model parameters prior to training and validation. We show that this approach results in accurate predictions within 3 cycles to end of life (EOL). We demonstrate the effectiveness of our approach by applying it to the N-CMAPSS turbofan engine dataset recently released by NASA, which includes high fidelity degradation modeling, real world operating conditions, and a large set of fault operating modes.

Prognostics↗
DOE OSTI2021

A Modeling Tool to Analyze the Performance of Industrial Cooling Towers

Energy efficiency and energy savings have become an important factor as industries look for ways to save energy and minimize their energy consumption while reducing their carbon footprint. Cooling towers are utilized significantly in industries for either serving chillers or process cooling. Depending on the size of the cooling tower, it can use a surprising amount of energy and water, which is why it is crucial to make sure that the facility has optimized their cooling tower.A modeling tool has been developed to perform a thorough analysis of a cooling tower and its various operations to ensure that the facility has optimized its cooling tower. This model analyzes an annual base case in comparison with the revised case of a cooling tower operation. This modeling tool simulates 8,760 hourly calculations for fan power for various fan controls, water consumption, and pumping energy consumption and demand based on the user’s location and its corresponding Typical Meteorological Year 3 (TMY3) weather data. This model is capable to simulate up to five cooling tower cells as one large tower utilizing one pump or parallel pumping. The successful validated cooling tower model should assist industry to save energy at their facility through their cooling tower, whether they use it for process cooling or heating, ventilation and air conditioning (HVAC) applications. The entering/leaving water temperatures based on a monthly operating schedule or a wet-bulb temperature schedule will be used as inputs, and the model can calculate savings in energy for various conditions including variable-frequency drive (VFD) on the fan/pump, drift eliminators, number of cycles of concentration, reduced water flow rate, etc.

Hooper, Josh↗
NASA NTRS1994

On the cause of the annual cycle in tropical lower-stratospheric temperatures

An analysis of monthly mean, zonally averaged temperatures from the lower-stratospheric channel of the microwave sounding unit (MSU-4) shows that on the month-to-month time scale, there is nearly complete compensation between temperature changes in the tropics and in the extratropics. For the annual cycle the MSU-4 data show a similar compensation between temperatures in the tropics and those in high latitudes, with only a small residual variation in the global mean. The tropics are coldest in January and warmest in July, compensating for the warmer wintertime temperatues in the Northern Hemisphere compared to those in the Southern Hemisphere. These out-of phase temperature variations betwen the tropics and extratropics are interpreted as the signature of an annual cycle in the strength of the wave-driven, Lagrangian mean meridional circulation, which warms the high-latitude winter hemisphere and cools the tropics. The observed phase of the annual cycle in tropical lower-stratospheric temperatures is thus determined by the stronger orographic and thermal forcing of the wintertime planetary waves in the Northern Hemisphere, which drives a stronger Lagrangian mean meridional circulation. In the absence of fluctuations in the global mean diabatic heating, the compensation would be complete and the globally averaged temperature would be constant. The small annual cycle in the globally averaged temperature in the MSU-4 data is nearly in phase with the annual cycle in the tropics and is consistent with the annual cycle in diabatic heating by ozone.

Yulaeva, Elena↗
DOE OSTI2022

Changes in global land use and CO 2 emissions from us bioethanol production: what drives differences in estimates between corn and cellulosic ethanol?

Land use change (LUC) CO 2 emissions associated with bioenergy production depend on the amount of land required to produce bioenergy crops, the carbon stored in such crops (including in the leaves, stalk, roots and soil), and the carbon emitted when another land cover is directly or indirectly displaced as a result. In this study, we use a global integrated assessment model [the Global Change Analysis Model (GCAM)] to explore the differences in estimates of LUC CO 2 emissions for two crops (corn and switchgrass) used to produce ethanol in the United States under alternative assumptions about natural lands protection. Varying the latter assumptions for corn ethanol results in net LUC CO 2 emissions between 7 and 41 gCO 2 per MJ of ethanol, whereas varying the same assumptions for switchgrass ethanol results in net emissions between -26 and 14 gCO 2 per MJ of ethanol. The low-end estimate for each occurs when natural lands are assumed to be fully protected everywhere, which leads to significant cropland intensification. The high-end estimate for each occurs when natural lands are assumed to be unprotected everywhere, leading to greater cropland expansion and associated conversion of unmanaged forest and pasture. Results from this study could be used to inform scenarios of future energy system change or life cycle assessment of biofuels for which LUC emissions would be an input.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2010

Projected Applications of a "Climate in a Box" Computing System at the NASA Short-Term Prediction Research and Transition (SPoRT) Center

The NASA Short-term Prediction Research and Transition (SPoRT) Center focuses on the transition of unique observations and research capabilities to the operational weather community, with a goal of improving short-term forecasts on a regional scale. Advances in research computing have lead to "Climate in a Box" systems, with hardware configurations capable of producing high resolution, near real-time weather forecasts, but with footprints, power, and cooling requirements that are comparable to desktop systems. The SPoRT Center has developed several capabilities for incorporating unique NASA research capabilities and observations with real-time weather forecasts. Planned utilization includes the development of a fully-cycled data assimilation system used to drive 36-48 hour forecasts produced by the NASA Unified version of the Weather Research and Forecasting (WRF) model (NU-WRF). The horsepower provided by the "Climate in a Box" system is expected to facilitate the assimilation of vertical profiles of temperature and moisture provided by the Atmospheric Infrared Sounder (AIRS) aboard the NASA Aqua satellite. In addition, the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard NASA s Aqua and Terra satellites provide high-resolution sea surface temperatures and vegetation characteristics. The development of MODIS normalized difference vegetation index (NVDI) composites for use within the NASA Land Information System (LIS) will assist in the characterization of vegetation, and subsequently the surface albedo and processes related to soil moisture. Through application of satellite simulators, NASA satellite instruments can be used to examine forecast model errors in cloud cover and other characteristics. Through the aforementioned application of the "Climate in a Box" system and NU-WRF capabilities, an end goal is the establishment of a real-time forecast system that fully integrates modeling and analysis capabilities developed within the NASA SPoRT Center, with benefits provided to the operational forecasting community.

Jedlovec, Gary J.↗
DOE OSTI2020

Long-Term Vehicle Speed Prediction via Historical Traffic Data Analysis for Improved Energy Efficiency of Connected Electric Vehicles

Connected and automated vehicles (CAVs) are expected to provide enhanced safety, mobility, and energy efficiency. While abundant evidence has been accumulated showing substantial energy saving potentials of CAVs through eco-driving, traffic condition prediction has remained to be the main challenge in capitalizing the gains. The coupled power and thermal subsystems of CAVs necessitate the use of different speed preview windows for effective and integrated power and thermal management. Real-time vehicle-to-infrastructure (V2I) communications can provide an accurate speed prediction over a short prediction horizon (e.g., 30 s to 60 s), but not for a long range (e.g., over 180 s). Therefore, advanced approaches are required to develop detailed speed prediction for robust optimization-based energy management of CAVs. This paper presents an integrated speed prediction framework based on historical traffic data classification and real-time V2I communications for efficient energy management of electrified CAVs. The proposed framework provides multi-range speed predictions with different fidelity over short and long horizons. The proposed multi-range speed prediction is integrated with an economic model predictive control (MPC) strategy for the battery thermal management (BTM) of connected and automated electric vehicles (EVs). The simulation results over real-world urban driving cycles confirm the enhanced prediction performance of the proposed data classification strategy over a long prediction horizon. Despite the uncertainty in long-range CAVs’ speed predictions, the vehicle-level simulation results show that 14% and 19% energy savings can be accumulated sequentially through eco-driving and BTM optimization (eco-cooling), respectively, when compared with normal driving (i.e., human driver) and conventional BTM strategy.

Engineering↗
DOE OSTI2025

Deletion of Re -citrate synthase allows for analysis of contributions of tricarboxylic acid cycle directionality to the growth of Heliomicrobium modesticaldum

ABSTRACT Heliomicrobium modesticaldum,a phototrophic member of the phylum Firmicutes and family Clostridiales, possesses most of the enzymes specific to the reductive tricarboxylic acid (rTCA) cycle, except for the key enzyme, ATP-citrate lyase. It is thought to utilize a split TCA cycle when growing on pyruvate as a carbon source, in which the oxidative TCA (oTCA) direction generates most of the 2-ketoglutarate, but some can be produced in the reductive direction. Although a typicalSi-citrate synthase gene is not found in the genome, it was suggested that gene HM1_2993, annotated as homocitrate synthase, actually encodesRe-citrate synthase, which would function as the initial enzyme of the oTCA cycle. We deleted this gene to test this hypothesis and, if true, see what effect severing access to the oTCA cycle would have on this organism. The endogenous CRISPR-Cas system was used to replace the open reading frame with a selectable marker. The deletion mutants could grow on pyruvate but were unable to grow phototrophically on acetate + CO 2 as carbon source. Growth on acetate could be rescued by the addition of different electron sources (formate or ascorbate), suggesting that the oTCA cycle is used to oxidize acetate to generate electrons required to drive the carboxylation of acetyl-CoA. The deletion mutants were capable of growing in acetate minimal media without additional organic supplements beyond formate, demonstrating that the rTCA cycle can be employed to support sufficient 2-ketoglutarate production in this organism, unlike citrate synthase mutants in several chemoheterotrophic organisms utilizing the oTCA cycle. IMPORTANCE Heliobacteria are a unique group of phototrophic bacteria that are obligate anaerobes and possess a rudimentary system to use light as a source of energy. They do not make oxygen or fix carbon dioxide. Here, we explore their fundamental carbon metabolism to understand the role and operation of the central TCA cycle. This work shows both the role and operation of this cycle under different growth modes and explains how these organisms can obtain electrons to drive their biosynthetic metabolism. This foundational knowledge will be crucial in the future when attempts are made to use this organism as a platform for oxygen-sensitive synthesis of compounds in an anaerobe that can use light as its energy source.

Biotechnology & Applied Microbiology↗
DOE OSTI2023

Hybrid Heavy Duty Diesel Powertrain for Off-Road Applications (Final Technical/Scientific Report)

In this program, a heavy-duty hybrid powersystem, consisting of a 30% downsized diesel engine and a front-end accessory drive (FEAD) incorporating a high-speed flywheel (HSFW) energy storage system, a mechanical-drive turbocharger (SuperTurbo), and motor-generator units (MGU) was developed and demonstrated. The high efficiency core 13L engine coupled with the hybrid elements was physically validated across various off-road machine and transient work cycles with the ultimate goal of demonstrating 17% efficiency improvement with equivalent transient response as the 18L diesel engine this concept powersystem would replace. The project culminated in a physical demonstration of the high-efficiency powersystem in a high-capability test cell with the engine, all the hybrid devices, controls, and required performance and emissions measurements. Based on the combination of physical validation and rigorous system simulation, the following program conclusions may be drawn: (1) The developed hybrid H2D2 powersystem demonstrated a range of efficiency improvement of 10.5 - 25.6%, with a midpoint of 17.9%; (2) Transient load response on; (3) The HSFW system was validated to achieve peak assisting of 110kW at 12,000 Nm/sec ramp rates; (4) The powersystem was validated to be capable of meeting U.S. EPA Tier 4 Final off-road emissions through transient NRTC testing; (5) A Total Cost of Ownership (TCO) analysis and found that the core 13L engine would pay back immediately (adoption of start/stop would pay back in less than one year, and the full hybrid system payback was three years.)

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2019

A Study of the 20 Day Superorbital Modulation in the High-Mass X-Ray Binary IGR J16493-4348

We report on Nuclear Spectroscopic Telescope Array (NuSTAR), Neil Gehrels Swift Observatory(Swift) X-ray Telescope (XRT), and Swift Burst Alert Telescope (BAT) observations of IGR J16493-4348, a wind-fed supergiant X-ray binary showing significant superorbital variability. From a discrete Fourier transform of the BAT light curve,we refine its superorbital period to be 20.058±0.007 days. The BAT dynamic power spectrum and a fractional root mean square analysis both show strong variations in the amplitude of the superorbital modulation, but no observed changes in the period are found. The superorbital modulation is significantly weaker between MJD 55,700 and MJD 56,300. The joint NuSTAR and XRT observations, which were performed near the minimum and maximum of one cycle of the 20 day superorbital modulation, show that the flux increases by more than a factor of two between superorbital minimum and maximum. We find no significant changes in the 3-50 keV pulse profiles between superorbital minimum and maximum, which suggests a similar accretion regime. Modeling the pulse-phase-averaged spectra we find a possible Fe Kα emission line at 6.4 keV at superorbital maximum. This feature is not significant at superorbital minimum. While we do not observe any significant differences between the pulse-phase-averaged spectral continua apart from the overall flux change, we find that the hardness ratio near the broad main peak of the pulse profile increases from superorbital minimum to maximum. This suggests the spectral shape hardens with increasing luminosity. We discuss different mechanisms that might drive the observed superorbital modulation.

Coley, Joel B.↗
DOE OSTI2022

Heavy-Duty Vehicle Activity Updates for MOVES Using NREL Fleet DNA and CE-CERT Data

The U.S. Environmental Protection Agency's (EPA's) Motor Vehicle Emission Simulator (MOVES) is a publicly available tool used by researchers and policymakers to help understand motor vehicle emission sources at a national, county, and project level. Estimates of heavy-duty activity in the most recent version of the model at the time this work was conducted, MOVES2014, was identified as an area in need of improvement. The start activity in MOVES2014 is based on a limited and dated data set. In addition, MOVES2014 relies on drive cycles that represent on-network activity but do not account for idling activity that occurs on off-network roads, such as at a distribution center, while the truck is queuing or during loading and unloading. As a result, MOVES2014 may currently underestimate the number of starts and idle and soak time for heavy-duty trucks in real-world operation. The National Renewable Energy Laboratory (NREL) has previously leveraged its expansive Fleet DNA database of heavy-duty vehicles to idle and start activity for six of the nine heavy-duty vehicle source types of classes in the MOVES model. The data available in Fleet DNA from 416 conventional, diesel-powered vehicles provided activity estimates from more than 120,000 hours of operation throughout 14,682 vehicle days between October 2006 and January 2016. NREL calculated start fraction, starts per day, soak fraction, and idle fraction by hour of the day for each vehicle type, state, and vocation, and provided results in .CSV files that can be translated to MOVES table inputs. The idle and start activity from this initial analysis of Fleet DNA data was used to develop default idle and start data for heavy-duty vehicles in MOVES3. Satisfied with the results from the Fleet DNA data used for MOVES3, the EPA asked NREL to extend this start/soak/idle analysis using additional data from a larger number of vehicles for a potential future update to the MOVES model. Such a data set was achieved from a project led by the University of California at Riverside, College of Engineering, Center for Environmental Research & Technology (CE-CERT) and funded by California Air Resources Board. Specifically, this data set consists of 90 heavy-duty vehicles operated mainly in California, which can be separated into five of the nine heavy-duty vehicle classes in the MOVES model. In addition, the heavy-duty activity database collected by CE-CERT provided activity estimates from more than 44,000 hours of operation throughout 4,724 vehicle days between November 2014 and September 2016. This report details the analysis of the heavy-duty activity database collected from the University of California at Riverside by providing graphical analysis and context for the start, soak, and idle distributions. The comparison of the related results from both the Fleet DNA and CE-CERT data sets are documented as well.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2014

MARGInS: Model-Based Analysis of Realizable Goals in Systems

Under NASAs Constellation effort, the Exploration Technology Development Program funded research toward a system validation capability that applied machine learning and test-case generation techniques to the analysis of black-box system behavior. The behavior analysis capability scaled to spaces of hundreds of input parameters and tens of thousands of test cases. Aerospace systems at the vehicle level, especially those systems which contain some level of autonomy, are best described by hybrid and non-linear mathematics. Even simplified models of such systems need parameter dimensionalities in the hundreds or thousands of parameters in order to capture sufficient fidelity. The System Safety Assessments (such as those described in the SAE ARP 4761A Safety Assessment Process guidelines) for these systems are prone to errorinteractions between the vehicles subsystems are complex, and can display emergent behaviors. NASA captured this new analysis in the Model-based Analysis of Realizable Goals in Systems (MARGInS) tool and applied it to the Pad Abort 1 (PA-1) simulation as part of the independent validation and verification cycle before the PA-1 flight test in May of 2010. MARGInS evaluated the adherence of the high-fidelity simulation to its requirements, and deter- mined the margins to failure from the expected nominal input conditions. Following the PA-1 test, the capabilities within the MARGInS framework have been extended with sophisticated statistical and white-box test case generation techniques and applied to other NASA missions. The frame- work now includes a critical factors analysis that was applied to NASAs Orion simulation and design. NASAs Aeronautics Research Mission Directorate (ARMD) leveraged the existing MARGInS framework for work on aviation safety for civil transport vehicles and for research on autonomy issues. The NASA ARMD effort created a time series output prediction capability that has been used to characterize trajectories for a plane with an adaptive control system, and a safety boundary detection capability that has been applied to an air traffic control concept of operation for the Federal Aviation Administration. The statistical and machine- learning based techniques within MARGInS have been successfully combined with concolic execution to improve the coverage of a critical unit by driving system-level inputs. The use case driving the concolic execution and MARGInS integration was inspired by the Air France 447 disaster in which the loss of a critical functionality (the airspeed calculation from the pitot tubes) led to loss of the entire plane with the people aboard. To illustrate capabilities and limitations, we will highlight the analyses for the applications listed above. We will then discuss the future plans for MARGInS and its interfaces with other tools.

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