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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Robust integrated neurocontroller for complex dynamic systems

The goal of this research effort is to develop an integrated control software environment for the purpose of creating an intelligent neurocontrol system. The system will be capable of estimating states, identifying parameters, diagnosing conditions, planning control strategies, and producing intelligent control actions. The distinct features of such control system are adaptability and on-line learning capability. The proposed system will be flexible to allow structure adaptability to account for changes in the dynamic system such as sensory failures and/or component degradations. The developed system should learn system uncertainties and changes, as they occur, while maintaining minimal control level on the dynamic system. The research activities set to achieve the research objective are summarized by the following general items: (1) Development of a system identifier or diagnostic system; (2) Development of a robust neurocontroller system, and; (3) Integration of above systems to create a robust Integration Control system (RIC-system). Two contrary approaches are investigated in this research: classical (traditional) design approach, and the simultaneous design approach. However, in both approaches neural network is the base for the development of different functions of the system. The two resulting designs will be tested and simulation results will be compared for better possible implementation.

Zein-Sabbato, S.↗
NASA NTRS1996

Robust Integrated Neurocontroller for Complex Dynamic Systems

The goal of this research effort is to develop an integrated control software environment for the purpose of creating an intelligent neurocontrol system. The system will be capable of estimating states, identifying parameters, diagnosing conditions, planning control strategies, and producing intelligent control actions. The distinct features of such control system are: adaptability and on-line learning capability. The proposed system will be flexible to allow structure adaptability to account for changes in the dynamic system such as: sensory failures and/or component degradations. The developed system should learn system uncertainties and changes, as they occur, while maintaining minimal control level on the dynamic system. The research activities set to achieve the research objective are summarized by the following general items: (1) Development of a system identifier or diagnostic system, (2) Development of a robust neurocontroller system, and 3. Integration of above systems to create a Robust Integrated Control system (RIC-system). Two contrary approaches are investigated in this research: classical (traditional) design approach, and the simultaneous design approach. However, in both approaches neural network is the base for the development of different functions of the system. The two resulting designs will be tested and simulation results will be compared for better possible implementation.

Zein-Sabatto, S.↗
DOE OSTI2023

A machine learning approach targeting parameter estimation for plant functional type coexistence modeling using ELM-FATES (v2.0)

Tropical forest dynamics play a crucial role in the global carbon, water, and energy cycles. However, realistically simulating the dynamics of competition and coexistence between different plant functional types (PFTs) in tropical forests remains a significant challenge. This study aims to improve the modeling of PFT coexistence in the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a vegetation demography model implemented in the Energy Exascale Earth System Model (E3SM) land model (ELM), ELM-FATES. Specifically, we explore (1) whether plant trait relationships established from field measurements can constrain ELM-FATES simulations and (2) whether machine learning (ML)-based surrogate models can emulate the complex ELM-FATES model and optimize parameter selections to improve PFT coexistence modeling. We conducted three ensembles of ELM-FATES experiments at a tropical forest site near Manaus, Brazil. By comparing the ensemble experiments without (Exp-CTR) and with (Exp-OBS) consideration of observed trait relationships, we found that accounting for these relationships slightly improves the simulations of water, energy, and carbon variables when compared to observations but degrades the simulation of PFT coexistence. Using ML-based surrogate models trained on Exp-CTR, we optimized the trait parameters in ELM-FATES and conducted another ensemble of experiments (Exp-ML) with these optimized parameters. The proportion of PFT coexistence experiments significantly increased from 21 % in Exp-CTR to 73 % in Exp-ML. After filtering the experiments that allow for PFT coexistence to agree with observations (within 15 % tolerance), 33 % of the Exp-ML experiments were retained, which is a significant improvement compared to the 1.4 % in Exp-CTR. Exp-ML also accurately reproduces the annual means and seasonal variations in water, energy, and carbon fluxes and the field inventory of aboveground biomass. This study represents a reproducible method that utilizes machine learning to identify parameter values that improve model fidelity against observations and PFT coexistence in vegetation demography models for diverse ecosystems. Our study also suggests the need for new mechanisms to enhance the robust simulation of coexisting plants in ELM-FATES and has significant implications for modeling the response and feedbacks of ecosystem dynamics to climate change.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

Combined Qualification Vibration Testing and Fixed Base Modal Testing Utilizing a Fixed Based Correction Method

Vibration testing spaceflight hardware is a vital, but time consuming and expensive endeavor. Traditionally modal tests are performed at the component, subassembly, or system level, preferably free-free with mass loaded interfaces or fixed base on a seismic mass to identify the fundamental structural dynamic (modal) characteristics. Vibration tests are then traditionally performed on single-axis slip tables at qualification levels that envelope the maximum predicted flight environment and workmanship in order to verify the spaceflight hardware can survive its flight environment. These two tests currently require two significantly different test setups, facilities, and ultimately reconfiguration of the spaceflight hardware. The vision of this research is to show how traditional fixed-base modal testing can be accomplished using vibration qualification testing facilities, which not only streamlines testing and reduces test costs, but also opens up the possibility of performing modal testing to untraditionally high excitation levels that provide for test-correlated finite element models to be more representative of the spaceflight hardware's response in a flight environment. This paper documents the first steps towards this vision, which is the comparison of modal parameters identified from a traditional fixed-based modal test performed on a modal floor and those obtained by utilizing a fixed based correction method with a large single-axis electrodynamic shaker driving a slip table supplemented with additional small portable shakers driving on the slip table and test article. To show robustness of this approach, the test article chosen is a simple linear weldment, whose mass, size, and modal parameters couple well with the dynamics of the shaker/slip table. This paper will show that all dynamics due to the shaker/slip table were successfully removed resulting in true fixed-base modal parameters, including modal damping, being successfully extracted from a traditional style base-shake vibration test setup.

Base-Shake↗
NASA NTRS2019

Combined Qualification Vibration Testing and Fixed Base Modal Testing Utilizing a Fixed Based Correction Method

Vibration testing spaceflight hardware is a vital, but time consuming and expensive endeavor. Traditionally modal tests are performed at the component, subassembly, or system level, preferably free-free with mass loaded interfaces or fixed base on a seismic mass to identify the fundamental structural dynamic (modal) characteristics. Vibration tests are then traditionally performed on single-axis slip tables at qualification levels that envelope the maximum predicted flight environment plus 3 dB and workmanship in order to verify the spaceflight hardware can survive its flight environment. These two tests currently require two significantly different test setups, facilities, and ultimately reconfiguration of the spaceflight hardware. The vision of this research is to show how traditional fixed-base modal testing can be accomplished using vibration qualification testing facilities, which not only streamlines testing and reduces test costs, but also opens up the possibility of performing modal testing to untraditionally high excitation levels that provide for test-correlated finite element models to be more representative of the spaceflight hardware's response in a flight environment. This paper documents the first steps towards this vision, which is the comparison of modal parameters identified from a traditional fixed-based modal test performed on a modal floor and those obtained by utilizing a fixed based correction method with a large single-axis electrodynamic shaker driving a slip table supplemented with additional small portable shakers driving on the slip table and test article. To show robustness of this approach, the test article chosen is a simple linear weldment, whose mass, size, and modal parameters couple well with the dynamics of the shaker/slip table. This paper will show that all dynamics due to the shaker/slip table were successfully removed resulting in true fixed-base modal parameters, including modal damping, being successfully extracted from a traditional style base-shake vibration test setup.

Winkel, James P.↗
NASA NTRS1991

Parameter estimation in space systems using recurrent neural networks

The identification of time-varying parameters encountered in space systems is addressed, using artificial neural systems. A hybrid feedforward/feedback neural network, namely a recurrent multilayer perception, is used as the model structure in the nonlinear system identification. The feedforward portion of the network architecture provides its well-known interpolation property, while through recurrency and cross-talk, the local information feedback enables representation of temporal variations in the system nonlinearities. The standard back-propagation-learning algorithm is modified and it is used for both the off-line and on-line supervised training of the proposed hybrid network. The performance of recurrent multilayer perceptron networks in identifying parameters of nonlinear dynamic systems is investigated by estimating the mass properties of a representative large spacecraft. The changes in the spacecraft inertia are predicted using a trained neural network, during two configurations corresponding to the early and late stages of the spacecraft on-orbit assembly sequence. The proposed on-line mass properties estimation capability offers encouraging results, though, further research is warranted for training and testing the predictive capabilities of these networks beyond nominal spacecraft operations.

Parlos, Alexander G.↗
DOE OSTI2015

An algorithmic calibration approach to identify globally optimal parameters for constraining the DayCent model

he accurate calibration of complex biogeochemical models is essential for the robust estimation of soil greenhouse gases (GHG) as well as other environmental conditions and parameters that are used in research and policy decisions. DayCent is a popular biogeochemical model used both nationally and internationally for this purpose. Despite DayCent’s popularity, its complex parameter estimation is often based on experts’ knowledge which is somewhat subjective. In this study we used the inverse modelling parameter estimation software (PEST), to calibrate the DayCent model based on sensitivity and identifi- ability analysis. Using previously published N2 O and crop yield data as a basis of our calibration approach, we found that half of the 140 parameters used in this study were the primary drivers of calibration dif- ferences (i.e. the most sensitive) and the remaining parameters could not be identified given the data set and parameter ranges we used in this study. The post calibration results showed improvement over the pre-calibration parameter set based on, a decrease in residual differences 79% for N2O fluxes and 84% for crop yield, and an increase in coefficient of determination 63% for N2O fluxes and 72% for corn yield. The results of our study suggest that future studies need to better characterize germination tem- perature, number of degree-days and temperature dependency of plant growth; these processes were highly sensitive and could not be adequately constrained by the data used in our study. Furthermore, the sensitivity and identifiability analysis was helpful in providing deeper insight for important processes and associated parameters that can lead to further improvement in calibration of DayCent model.

Corn yield↗
DOE OSTI2017

Effect of ELMS and disruptions on FNSF plasma-facing components

Previous work has addressed the thermomechanical and electromagnetic effects of ELMs and disruptions on plasma-facing components in conceptual, commercial fusion reactors. Given that the proposed Fusion Nuclear Science Facility (FNSF) will have different geometry and plasma parameters, it is necessary to address similar issues in that context. Hence, this paper presents two key results: the thermomechanical response of the first wall and divertor to expected FNSF ELMs and disruptions, and the electromagnetic response of all structures inside the FNSF vacuum vessel to a plasma current quench. Structures considered in the electromagnetic analyses include the vacuum vessel, blankets, structural ring (which supports many of the internal components), and all internal shells used for plasma stability and control. The first wall is a ferritic steel structure with a thin tungsten coating and the divertor is all tungsten. Properties used for the divertor are those of pure tungsten, though it is quite possible that some alloy or nanostructured material would be employed at some point. Both the first wall and divertor are gas-cooled, so coolant pressures are quite high (8–10 MPa). The finite element code ANSYS is used to carry out all analyses and parametric studies are employed in order to identify parameters for which uncertainties will have a significant effect on the predicted performance. The ELM and disruption loads are found to be substantially smaller than those expected in a commercial reactor, so the component designs have more margin.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Thermographic process monitoring in powderbed based additive manufacturing

Selective Laser Melting is utilized to build metallic parts directly from CAD-Data by solidification of thin powder layers through application of a fast scanning laser beam. In this study layerwise monitoring of the temperature distribution is used to gather information about the process stability and the resulting part quality. The heat distribution varies with different kinds of parameters including scan vector length, laser power, layer thickness and inter-part distance in the job layout which in turn influence the resulting part quality. By integration of an off-axis mounted uncooled thermal detector the solidification as well as the layer deposition are monitored and evaluated. Errors in the generation of new powder layers usually result in a locally varying layer thickness that may cause poor part quality. For effect quantification, the locally applied layer thickness is determined by evaluating the heat-up of the newly deposited powder. During the solidification process space and time-resolved data is used to characterize the zone of elevated temperatures and to derive locally varying heat dissipation properties. Potential quality indicators are evaluated and correlated to the resulting part quality: Thermal diffusivity is derived from a simplified heat dissipation model and evaluated for every pixel and cool-down phase of a layer. This allows the quantification of expected material homogeneity properties. Maximum temperature and time above certain temperatures are measured in order to detect hot spots or delamination issues that may cause a process breakdown. Furthermore, a method for quantification of sputter activity is presented. Since high sputter activity indicates unstable melt dynamics this can be used to identify parameter drifts, improper atmospheric conditions or material binding errors. The resulting surface structure after solidification complicates temperature determination on the one hand but enables the detection of potential surface defects on the other hand. These issues and proper key figures for thermographic monitoring of the Selective Laser Melting process are discussed in the paper. Even though microbolometric temperature measurement is limited to repetition rates in the Hz-regime and sub megapixel resolution, current results show the feasibility of process surveillance by thermography for a limited section of the building platform in a commercial system.

42 ENGINEERING↗
DOE OSTI2024

Climate adaptation and sustainability in switchgrass: exploring plant-microbe-soil interactions across continental scale environmental gradients

Less carbon-intensive energy sources are needed to reduce greenhouse gas emissions and their predicted role in climate change. There is growing interest in the potential of biofuels for meeting this need. A critical question is whether large-scale biofuel production can be sustainable over the time scales needed to mitigate our carbon debt from fossil fuel consumption. The carbon balance and ultimately the sustainability of biofuel feedstock production is the result of complex climate-coupled interactions between carbon fixation, sequestration, and release through combustion. Similarly, the long-term productivity of biofuels depends on the environmental factors limiting plant growth. These factors are often related to soil resources which involve complex interactions at the plant-microbe-soil interface impacting their availability and cycling. Our collaborative project addressed sustainable switchgrass (Panicum virgatum) production by exploring Plant Systems, Plant-Microbiome Interactions, and Ecosystem Processes through the integrating lens of Multi-Scale Modeling. Our research was based on detailed characterization of genetically diverse switchgrass genotypes planted in common gardens across a continental latitudinal gradient. The underlying theme of our Plant Systems research was the use of locally adapted plant material to explore plant function, to understand the mechanistic basis of environmental interactions, and to discover the plant genes important for adaptation and sustainability in the face of climate change. Our Plant-Microbiome Interaction project characterized the microbial communities associated with switchgrass using genomic tools. Our Ecosystem Processes research focused on carbon cycle responses at the ecosystem level using stand level plantings. Finally, our Multi-Scale Modeling helped to define conditions of a sustainable biofuel system and identify key tradeoffs between genetic diversity, productivity, and ecosystem services. Genome-wide association analyses were used to identify alleles that contribute to successful establishment and biomass production across North America. Together, our work provided a baseline analyses of the potential of switchgrass as a biofuel feedstock. Our project resulted in a number of successful outcomes. First, we were successful in collecting switchgrass germplasm across the species range, propagating the material, and establishing common garden experiments across the species range. In collaboration with DOE JGI, we successfully assembled the first tetraploid switchgrass genome and published this resource with an analyses of the genetic basis local adaptation from our gardens (Lowry et al. 2019, Lovell et al. 2021). The gardens were used to characterize the genetic architecture for a number of important plant phenotypes. Our project also conducted extensive sampling and sequencing to characterize the bacterial and fungal associates of switchgrass roots and leaves. We showed that host genotype, location, and harvesting practices can play a role in microbiome assembly (Singer et al. 2019 & 2022, Van Wallendael et al. 2020 & 2022, Edwards et al. 2023). Our ecosystem processes work created baseline dataset of carbon and nutrient cycling in realistic stand plantings of switchgrass. Data from this experiment provided new insight into the role of plant traits, phenology, and local environments in ecosystem processes like soil respiration, net-ecosystem exchange, and dynamics of soil and plant nutrients (Ricketts et al. 2023). Finally, our crop modelling experiments help to characterize the sensitivity of common modeling frameworks to parameters, identify key limiters of productivity across large geographic scales, and leverage patterns of local adaptation in prediction. Ultimately, these studies help to identify critical plant-microbe-soil traits that may be manipulated, through breeding or agronomic management, to improve the sustainability of biofuel feedstocks.

09 BIOMASS FUELS↗
NASA NTRS2014

Effects of Long Duration Spaceflight on Venous and Arterial Compliance

The visual impairment and intracranial pressure syndrome (VIIP) is a newly described space flight-associated medical condition made up of a constellation of symptoms affecting at least 34% of American astronauts who have flown International Space Station (ISS) missions. VIIP is defined primarily by visual acuity deficits and anatomical changes to eye structures, and is thought to be related to elevated intracranial pressure secondary to space flightinduced cephalad fluid shifts. Loss of visual acuity could be a significant threat to crew health and performance and may be suggestive of other adaptations with implications for years post-flight. Our primary objective is to determine whether vascular compliance is altered by space flight and whether such adaptations are related to the incidence of VIIP. In particular, we will measure ocular parameters and vascular compliance in vessels of the head and neck in astronauts who have no space flight experience, in astronauts before, during, and after space flight, and in bed rest subjects with conditions similar to space flight. Additionally, we will analyze astronaut data from the Lifetime Surveillance of Astronaut Health (LSAH) archive to determine which factors might be predictive of the development of VIIP. The project will be conducted in four separate but related parts. To understand the baseline condition of astronauts without any prior space flight experience, we will study 10 astronauts who have never flown in space by performing a comprehensive evaluation of the vasculature of the head, neck and eyes. Hemodynamic data (stroke volume and blood pressure), ocular (tonometry and ocular ultrasound), venous and arterial parameters will be acquired across a range of tilt angles (20, 10, 0, -10, -20 degrees). Vessels to be studied include the temporal, jugular, and vertebral veins and the cerebral, carotid and vertebral arteries. Ophthalmic data from the annual physical will be obtained through data sharing. To examine the relation between vascular compliance in the head and neck and the development of VIIP after a long duration space flight, we will study 10 astronauts before, during, and after long-duration ISS missions. Pre- and post-flight testing will be identical to that described above. During flight, images of the same vessels of interest will be obtained for later analysis. Ophthalmic data including VIIP scores will be obtained through data sharing from medically-required tests. To investigate the effects of age and elevated sodium intake, two potential contributors to VIIP, we will study 24 men (in two age groups: 25-35 and 45-55) during a 14 day 6deg head-down bed rest, a well-accepted analog of space flight. Standard NASA bed rest conditions will be maintained except for dietary sodium. Sodium intake will be similar to that of ISS astronauts, which is higher than consumed in previous bed rest studies. Pre- and post-bed rest testing procedures will be identical to the testing protocol described above for astronauts. Ophthalmic testing (optical coherence tomography, fundoscopy, and tonometry) will be conducted on the same day that vascular compliance measures are obtained. To identify parameters that may relate to an increase in an astronaut's susceptibility to developing VIIP, we will use data mining techniques to evaluate astronaut data obtained from the LSAH. Medical history, family history, space flight history and its related exposures, and history of high performance jet aircraft exposure will be examined for their potential relationship to ocular data. We hypothesize that the cephalad fluid shift induced by space flight will result in structural and functional adaptations in head and neck vessels leading to decreased vascular compliance and related to the development of VIIP symptoms. Further, although VIIP has not been observed in previous bed rest studies, we hypothesize that an elevated sodium intake will increase the incidence of VIIP symptoms in this space flight analog. Finally, we hypothesize that data mining analyses will reveal relationships between health history, previous exposures (including space flight and high performance aircraft), and the development of VIIP in the astronaut population.

Ribeiro, L. C.↗
DOE OSTI2019

Monitoring Potential Transport of Radioactive Contaminants in Shallow Ephemeral Channels: FY2018

Desert Research Institute (DRI) is conducting a field assessment of the potential for contaminated soil to be transported from the Smoky Site Contamination Area (CA) as a result of storm runoff. This activity supports U.S. Department of Energy (DOE) Environmental Management Nevada Program (EM NV) efforts to establish post-closure monitoring plans for the Smoky Site Soils Corrective Action Unit (CAU) 550. The work is intended to confirm the likely mechanism of transport and determine the meteorological conditions that might cause the movement of contaminated soils, as well as determine the particle size fraction that is most closely associated with transported radionuclide-contaminated soils. These data will facilitate the design of the appropriate post-closure monitoring program. In 2011, DRI installed a meteorological monitoring station on the west side of the Smoky Site CA and a hydrologic (runoff) monitoring station within the CA, near the east side. The meteorological station collects air temperature, wind speed, wind direction, relative humidity, precipitation, solar radiation, barometric pressure, soil temperature, and soil water content data. The maximum, minimum, and average or total values (as appropriate) for each of these parameters are recorded for each 10-minute interval. The maximum, minimum, and average water depth in the flume installed at the hydrologic station are also recorded for each 10-minute interval. This report presents the data collected from these stations during fiscal year (FY) 2018. During the FY2018 reporting period, the warmest months were June, July, and August and the coldest were December through March. Solar radiation showed the same seasonal trend. Monthly mean wind speeds were highest in the spring (March through May) and early summer (June). Winds were generally from the west during the summer and from the north throughout the fall and winter. The monthly average relative humidity ranged from the mid-teens to approximately 50 percent. Humidity was lowest in the fall and highest in the winter. Monthly total precipitation ranged from 0 in October, December, and June to approximately 1.38 inches (in) (35.05 millimeters [mm]) in July. Total precipitation for FY2018 was 3.86 in (98.04 mm). During the reporting period, two runoff events were recorded at the flume. One occurred on July 14, 2018, in response to precipitation earlier the same day. This event produced a peak water depth of 11.26 in (28.60 centimeters [cm]) in the flume, which is equivalent to a discharge of 1.86 cubic feet per second (cfs) (0.05 cubic meters per second [cm/s]) and a velocity of 3.97 feet per second (fps) (1.21 meters per second [m/s]) through the flume. Applying the flume hydraulic measurements to the channel geometry at the nearest surveyed cross-section it was determined that the velocity through the channel was 1.29 fps (0.39 m/s), which is sufficient to transport silts and fine sands. The second flow event occurred in response to earlier precipitation on September 4, 2018. This event produced a peak water depth of 0.78 in (1.98 cm) in the flume, which is equivalent to a discharge of 0.03 cfs (0.001 cm/s) and a velocity of 1.17 fps (0.36 m/s) through the flume. Applying the flume hydraulic measurements to the channel geometry at the nearest surveyed cross-section it was determined that the velocity through the channel was 0.03 fps (0.01 m/s). Although neither runoff event produced sufficient flow velocities through the natural channel to cause local erosion and transport of coarser bedload materials, the velocity of the first runoff event was sufficient to transport silts and fine sands, which have been shown to be preferentially associated with radionuclide contaminants. Therefore, a sampling event was planned after the first flow event in conjunction with a periodic maintenance inspection. As no suspended load sampling is available at this location, bedload samples were collected from the vicinity of the flume on August 7, 2018. The collected sediment was separated into three particle size fractions and each fraction was analyzed for americium-241 (Am-241), plutonium-238 (Pu-238), and plutonium-239/240 (Pu-239/240) by alpha spectrometry. The two smaller particle size fractions had higher concentrations of all three radionuclides than the largest particle size fraction. Additionally, Pu-239/240 had the highest concentration and Pu-238 had the lowest concentration in all samples. The same relationship between the concentrations of Pu-238 and Pu-239/240 was seen in samples reported in FY2013 and FY2014. Observation of meteorological and environmental conditions that lead to storm runoff will help identify parameters and threshold conditions that should be incorporated into postclosure monitoring plans for this and similar sites as well as aid in determining appropriate closure strategies for other Soils CAUs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Association‐based activity coefficient model for electrolyte solutions

Abstract This work presents an association‐based activity coefficient model that explicitly considers the solution nonideality due to associations among ions and solvent species. Built upon the electrolyte nonrandom two‐liquid (eNRTL) model, the model greatly improves the accuracy of eNRTL model for strongly associating electrolyte solutions due to presence of ionic species with high surface charge density. The model successfully correlates mean ionic activity coefficients of 46 aqueous single‐salt systems from 10 cations and 5 anions at 298.15 K up to their solubility limits. With the ion‐specific association parameters identified, the model accurately predicts activity and osmotic coefficients for aqueous mixed‐salt systems at 298.15 K. The temperature dependence of the model results has also been examined at 273–373 K. With superior accuracy over a wide range of concentration and temperature, the model represents a major advancement over eNRTL model and has a great potential to be a next‐generation model for electrolyte solutions.

Lin, Yu‐Jeng↗
DOE OSTI2015

General squark flavour mixing: constraints, phenomenology and benchmarks

Here, we present an extensive study of non-minimal flavour violation in the squark sector in the framework of the Minimal Supersymmetric Standard Model. We investigate the effects of multiple non-vanishing flavour-violating elements in the squark mass matrices by means of a Markov Chain Monte Carlo scanning technique and identify parameter combinations that are favoured by both current data and theoretical constraints. We then detail the resulting distributions of the flavour-conserving and flavour-violating model parameters. Based on this analysis, we propose a set of benchmark scenarios relevant for future studies of non-minimal flavour violation in the Minimal Supersymmetric Standard Model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

On the hot surface ignition of a wall-stagnating spray flame

The ignition of fuel sprays due to interaction with hot surfaces is an important phenomenon in the safety analysis of many engineering systems. We perform a parametric study of the hot surface ignition (HSI) of a fuel spray approaching a heated surface caused by the accidental leakage of a fuel line. Here, to this end, we employ a one-dimensional Eulerian-Eulerian formulation with a non-equilibrium evaporation model and a realistic chemical mechanism to describe $n$-dodecane fuel chemistry. We first describe and analyze the phenomenology of the unsteady processes leading to ignition using non-dimensionalized quantities. Through consideration of the temporal development of the most reactive mixture, we demonstrate that ignition occurs at a fuel-lean composition in a premixed region near the hot surface. Using non-dimensional parameters identified from the governing equations, we perform a parametric study of the time, location and local mixture composition at ignition and determine the ignition limits. We then identify the most important parametric sensitivities for physical analysis using a data-driven classification method. Our analysis demonstrates a contraction of the ignition limits with increased Stokes number and a regime of parametric insensitivity of igniting mixture composition. We also show that at high Damköhler numbers, the ignition location conforms to the parametric behavior of the thermal boundary layer, whereas at low Damköhler numbers approaching the ignition limit it reaches a near-unity value of the quenching Peclet number. We then compare the demonstrated parametric dependencies to the results of the quasi-steady asymptotic ignition literature, showing that our results are consistent with those obtained analytically within the limitations imposed by the simplified formulation of the latter.

42 ENGINEERING↗
DOE OSTI2026

Employment access assessed using the mobility energy productivity (MEP) metric

Transit agencies, local governments, employers, and job-seekers have a shared interest in connecting residents with jobs in an affordable and time efficient manner, with public agencies also caring about energy efficiency and air quality. Employment hubs are an opportunity to solve the spatial mismatch between homes of job-seekers and the locations of desirable jobs. Such is the case in Columbus, Ohio, between Rickenbacker Industrial Park and the Linden neighborhood, which has experienced persistent poverty. Using the mobility energy productivity (MEP) metric to examine travel time, cost, and energy efficiency, we show current transit service is undesirable due to excessive travel time (70 min, MEP = 0), while driving alone (MEP = 0.20) may be less desirable than a hypothetical, fare-free microtransit service (MEP = 0.23). Updating MEP to use locally-derived input data can help identify parameters under which providing microtransit service in a specific place has compelling benefits in terms of vehicle energy efficiency as well as cost and travel time for riders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Model calibration and optimization of a post-combustion CO 2 WAG pilot in a mature oil field

A carbon dioxide (CO 2 ) water-alternating-gas (WAG) pilot was conducted to gain insights into tertiary oil recovery potential via CO 2 flood in the West Ranch Field as part of the Petra Nova project, the world's largest postcombustion CO 2 capture and utilization initiative. With a fluvial formation geology, this is a challenging and novel application of CO 2 enhanced oil recovery. The aim of this study is two-fold. First, to build a predictive dynamic model that incorporates the data acquired during the pilot operation. Second, to utilize this model to provide guidance for optimal design for a field-wide CO 2 EOR operation. Our study began with an initialization of the pilot sector model extracted from a calibrated full-field model. The pilot model calibration follows a two-step hierarchical workflow. First, we performed a large-scale update of the permeability distribution by integrating available bottomhole pressure and multiphase production data. Next, local permeability field is fine-tuned using a streamline-based method to match CO 2 breakthrough times at the producers. The predictive capability of the calibrated model was verified through two blind validation tests: (1) the model showed good agreement with saturation logs acquired at two observation wells; and (2) the model reproduced the CO 2 recovery as a fraction of the injected CO 2 . Sensitivity studies were conducted using the calibrated pilot model to evaluate the effects of various operational parameters. Finally, we performed a Design of Experiment based multi-objective optimization of the CO 2 WAG processes using the influential operational parameters identified from the sensitivity analysis.

02 PETROLEUM↗