Vapor Transport Analysis of a Chloride Molten Salt Flow Control Valve.
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Preparing transportation safety analysis reports for microreactors is time and labor intensive, requiring extensive cross referencing to Federal regulations, previously approved documents, and expert review comments across structural, thermal, criticality, shielding, containment, and security. These burdens are magnified by the novelty of microreactor technologies and the evolving regulatory landscape, as well as current workforce constraints. Generative AI and supporting machine learning tools present an opportunity to accelerate drafting timelines, lift generalized writing burdens, and systematically enforce regulatory adherence through retrieval augmented generation and other knowledge retrieval and mapping methods. This draft report presents a preliminary feasibility assessment of the use of AI to expedite the preparation of microreactor transportation safety analysis reports and proposes an initial methodology for doing so.
The road transportation of critical components for cryogenic cryomodules is a challenging task. Indeed, the shipping and the handling of fundamental sub-assemblies can expose these components to harmful dynamic loads that can jeopardize their structural integrity. This article has the purpose of developing a finite element multibody model capable of assessing the acceleration on a test coupler for a cavity of the Single Spoke Resonator 1 subjected to a typical road transportation trip. A multibody model consisting of rigid bodies and finite element–imported flexible bodies has been created allowing a comparison of the simulated and experimental acceleration. Afterwards, an experimental on-road test, whose set-up is described in this article, has been carried out at Fermilab with instrumented components. Being able to effectively simulate and validate the dynamic effects on such sub-assemblies makes it possible, for the future, to simulate more complex structures subject to dynamic loadings, such as the entire cryomodules during shipping. Furthermore, the results from the simulations can be used to guide the design of new suspension systems suitable for the reduction mitigation of structural vibration during the road transportation of cryomodules.
The main objectives of the composite analysis (CA) compliance case vadose zone (VZ) facet are to simulate transport of radionuclide releases from the surface to the water table, and to provide radionuclide transfer rates to groundwater for inclusion into the Plateau-to-River (P2R) saturated zone (SZ) model (CP-57037, Model Package Report: Plateau to River Groundwater Model, Version 8.3). The parallel exascale version of the Subsurface Transport Over Multiple Phases (eSTOMP) simulator is used to simulate flow and transport for the CA VZ models. The CA compliance case approach to address the scale and distribution of contaminant sources in the VZ facet is to subdivide the Hanford Site Central Plateau into 26 models that contain contaminant sources and liquid discharges likely to commingle during migration through the VZ to the water table.
Transportation safety, as a critical component of an efficient and reliable transportation system, has been extensively studied with respect to societal economic impacts by transportation agencies and policy officials. However, the embodied energy impact of safety, other than induced congestion, is lacking in studies. This research proposes an energy equivalence of safety (EES) framework to provide a holistic view of the long-term energy and fuel consequences of motor vehicle crashes, incorporating both induced congestion and impacts from lost human productivity resulting from injury and fatal accidents and the energy content resulting from all consequences and activities from a crash. The method utilizes a ratio of gross domestic product (GDP) to national energy consumed in a framework that bridges the gap between safety and energy, leveraging extensive studies of the economic impact of motor vehicle crashes. The energy costs per fatal, injury, and property-damage-only (PDO) crashes in gasoline gallon equivalent (GGE) in 2017 were found to be 200,259, 4442, and 439, respectively, which are significantly greater than impacts from induced congestion alone. The results from the motor vehicle crash data show a decreasing trend of EES per crash type from 2010 and 2017, due primarily in part to a decreasing ratio of total energy consumed to GDP over those years. In addition to the temporal analysis, we conducted a spatial analysis addressing national-, state-, and local-level EES comparisons by using the proposed framework, illustrating its applicability.
A “screening analysis” is implemented at Pahute Mesa (PM), Nevada National Security Site (NNSS), to determine subsets of the 43 radionuclides listed in the radionuclide inventory of Finnegan et al. (2016) that are of relevance or potential relevance to the hydrologic source term (HST) for assessment of radionuclide transport in groundwater. Consideration is added to how levels of contamination are defined and whether any other radionuclides not in the inventory are relevant to the HST. A model is developed to estimate a range of possible source concentrations in groundwater that account for uncertainty in partitioning into melt glass and sorption into surrounding rock of the exchange zone for the 82 PM underground nuclear tests detonated in vertical shafts. The model also accounts for the varied hydrogeochemical settings. Transport parameters needed for the screening model calculations are developed from databases for hydrogeologic units, chemistry, mineralogy, fracture spacing, fracture aperture, fracture openness, matrix porosity, bulk density, saturation, and alteration. Of key importance is consideration of diagenetic zonation of the mineralogy related to hydrothermal alteration. The screening analysis compares model results with available groundwater radiochemistry data. Consistency between screening model results and available data helps validate the model for application to all 43 radionuclides, most of which have no measurements or only non-detect measurements of concentration in groundwater. The screening analysis determines that ten radionuclides – tritium, Sr-90, I-129, Cs-137, U-232, U-233, U-234, U-238, and the total of Pu-239 and Pu-240 are relevant to the HST. Determination of relevance is primarily based on data and/or model results indicating source concentration exceeding a maximum contaminant level (MCL) out to 100 years since the time of detonation. U-238 is relevant to assessment of contamination relative to MCLs for uranium and gross alpha particle activity. Five other radionuclides – C-14, Cl-36, Tc-99, Np-237, and Pu-238 – are determined potentially relevant to the HST based on a 0.1 MCL threshold. The screening analysis recommends additional attention to the natural daughter radionuclides of the uranium series (U-238) and thorium series (Th-232) decay chains, particularly Ra-226 and Ra-228, that were not included the inventory.
Light-duty vehicles are the biggest contributor of carbon emissions in the transportation sector. This project uses the Automotive Deployment Options Projection Tool (ADOPT) to explore pathways to light-duty decarbonization through technology improvements being researched by the Department of Energies Vehicle Technology Office. It includes sensitivities to market conditions, such as proposed vehicle purchase incentives, and changes to the Corporate Average Fuel Economy and Greenhouse Gas regulations. The results suggest that achieving the Vehicle Technology Office's research goals will lead to one third of the annual carbon emissions by 2050, primarily through vehicle electrification.
To date, effective therapeutic treatments that confer strong attenuation against coronaviruses (CoVs) remain elusive. Among potential drug targets, the helicase of CoVs is attractive due to its sequence conservation and indispensability. We rely on atomistic molecular dynamics simulations to explore the structural coordination and dynamics associated with the SARS-CoV-2 Nsp13 apo enzyme, as well as their complexes with natural ligands. A complex communication network is revealed among the five domains of Nsp13, which is differentially activated because of the presence of the ligands, as shown by shear strain analysis, principal components analysis, dynamical cross-correlation matrix analysis, and water transport analysis. The binding free energy and the corresponding mechanism of action are presented for three small molecules that were shown to be efficient inhibitors of the previous SARS-CoV Nsp13 enzyme. Together, our findings provide critical fresh insights for rational design of broad-spectrum antivirals against CoVs.
Single-file diffusion (SFD) in finite open nanopores is characterized by nonzero spatially varying tracer diffusion coefficients within a generalized hydrodynamic description. This contrasts with infinite SFD systems where tracer diffusivity vanishes. In standard tracer counterpermeation (TCP) analysis, two reservoirs, each containing a different species, are connected to opposite ends of a finite pore. Here, we implement an extended TCP analysis to allow the two reservoirs to contain slightly different mixtures of the two species. Then, determination of diffusion fluxes through the pore allows extraction of diffusion coefficients for near-constant partial concentrations of the two species. This analysis is applied for a lattice-gas model describing two-component SFD through a finite linear pore represented by a one-dimensional array of cells. Two types of particles, A and B, can hop only to adjacent empty cells with generally different rates, $h_A$ and $h_B$. Particles are noninteracting other than exclusion of multiple cell occupancy. Results reveal generalized hydrodynamic tracer diffusion coefficients which adopt small values inversely proportional to pore length in the pore center, but which are strongly enhanced near pore openings.
A new approach to generate high-fidelity 3D microstructure reconstructions by leveraging resolution and sample volume characteristics from 2D and 3D microscopy methods is presented here. This approach is employed to model the microstructure of a highly orthotropic polypropylene separator used in lithium-ion batteries, which have challenging multi-scale features of fibrils (<100 nm) and lamellae (>100 nm) to resolve in 3D. Phase contrast nano X-ray computed tomographic data are used to reconstruct the lamellae phase, while 2D scanning electron microscopy data are used to characterize sub-100 nm microstructure features such as the thin fibrils that are beyond the effective resolution of X-ray computed tomography. Fibril geometries are reconstructed stochastically based on the 2D higher resolution data, and integrated with the lamellae geometries in 3D space. Transport property analyses are performed to investigate the bias of microstructure models without considering the fibrils. A sensitivity study is also conducted to facilitate understanding of the relationship between microstructure characteristics and transport properties.
Abstract As urban areas continue to expand and develop, categorizing cities into typologies offers a valuable framework for understanding metropolitan dynamics and fostering inter-city collaboration. However, existing typologies related to urban mobility have limitations, failing to consider cities within a single large urban region and often overlooking crucial dimensions such as trip demand and traffic flow. In this paper, we introduce a transportation-focused characterization for cities within a large urban region, specifically the San Francisco Bay Area, California. We incorporate over 40 metrics across five transportation dimensions: trip demand, road network, multi-modal network, traffic flow, and land use. Specifically, for the trip demand dimension, we include metrics capturing residents’ trip characteristics, such as mode share, intra-city trips, and inter-city trips. Additionally, we analyze the purpose of trips entering the city to gain a deeper understanding of incoming trip patterns. In the traffic flow dimension, we examine metrics like vehicle miles traveled, delay, and congestion to assess the traffic conditions on the street network. These, combined with other dimensions, provide a comprehensive view of a city’s transportation dynamics. Using unsupervised machine learning clustering methods, we identified eight distinct typologies for the Bay Area: Live Work Cities; Job and Activity Magnet Cities; Anchor Cities; Multi-modal Cities; Hyper-connected Cities; Low-density Residential Cities; Medium-density Residential Cities; and Mixed-use Residential Cities. Our findings show that many clusters are strongly influenced by trip demand and traffic flow metrics. Finally, we examine the practicality of this typology and its potential to guide collaborative transportation management strategies. The typologies provide a foundation for dialogue among Bay Area cities, focusing on evaluating shared characteristics and leveraging successes or challenges to develop unified strategies for transportation management.
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An accurate magnetohydrodynamic (MHD) equilibrium reconstruction is an essential starting point for stability and transport plasma analysis. Herein this work describes an approach for obtaining kinetic equilibrium reconstructions using the OMFIT framework, which has been applied for the first time to spherical tokamak data from NSTX and NSTX-U. The EFIT equilibrium solver is integrated with experimental data analysis procedures and subsequent TRANSP transport simulations to enhance the accuracy of the reconstruction, in particular, at the edge region, by adding constraints on the total pressure and current density profiles, based on the transport code solution. The accuracy of the equilibrium reconstruction depends on the uncertainty and number of constraints, as well as the choice of basis functions to represent the pressure and current density profiles. Improved fidelity of the equilibrium reconstruction is demonstrated by reducing the variability of the magnetic axis and boundary locations from several centimeters, for reconstructions based on magnetic and experimental pressure constraints, to only several millimeters, for kinetic reconstructions based on transport code constraints, when different representations of basis functions were tested. The variability of the safety factor on axis was reduced ten times in the same sensitivity study. The accuracy of the equilibrium reconstruction and subsequent mapping of the experimental kinetic profile data have a significant impact on the trapped gyro Landau fluid and linear CGYRO turbulence simulations, which predict different spectra of unstable modes and turbulent fluxes for cases with different numbers of constraints in the equilibrium reconstruction. Conversely, the stability analysis performed using the GATO code shows plasmas that are stable to n = 1 MHD modes in both equilibria using magnetic and experimental pressure constraints as well as the transport code constrained equilibrium. However, a scan of parameters away from these conditions shows considerable deviation in the threshold of unstable modes between these reconstructions. Therefore, for reliable plasma analysis and use in turbulence and stability calculations, a high-fidelity equilibrium reconstruction with accurate kinetic constraints based on transport code solutions is necessary.
The distance a solid biomass feedstock could be used to transport the feedstock when used as biobased fuel is critical information for transportation analysis. However, this information is not available. The break-even transportation distance (BTD) of various fuels from biomass feedstocks and fossil sources was analyzed for truck, rail, and ship transport modes based on bulk density, moisture content, and specific energy. Fourteen different biomass feedstocks, such as crop residues (e.g., corn stover), woody biomass (e.g., wood chips), including thermally pretreated (torrefied) and densified forms (pellets), cattle feedlot compost, and three standard fossil fuels, namely, coal, lignite, and diesel, were considered for BTD analysis and comparison. The BTD values were derived by comparing the energy content of biomass feedstocks with the energy expended in transporting the fuels through selected transportation modes. For ready reference, an alternative derivation of BTD equations and example calculations were also presented. Among the biomass feedstocks, torrefied pellets had the highest BTD (4.16 × 10 4 , 12.47 × 10 4 , and 54.14 × 10 4 km), and cattle feedlot compost had the lowest BTD (1.29 × 10 4 , 3.88 × 10 4 , and 9.23 × 10 4 km), respectively, for truck, rail, and ship. Higher bulk density and higher specific energy of the biomass feedstocks increased the BTD for all modes of transport. Transport is most efficient when mass-limited. Biomass feedstock bulk densities where transportation becomes mass-limited are 223, 1,480, and 656 kg/m 3 for truck, rail, and ship, respectively. Truck transport is typically mass-limited (payload limit restriction; increased BTD), whereas rail transport is entirely volume-limited (cargo space restriction; decreased BTD), and ship transport is mostly volume-limited for biomass feedstocks and mass-limited for densified biomass feedstocks. Ship transport is the most efficient, followed by rail and truck; on average for the materials (17) studied, rail is 3.1 times and ship is 9.2 times the truck's BTD. Based on the bulk density and higher specific energy of the biomass feedstocks, regardless of the refinery location, interstate truck transport of these feedstocks is not a limiting factor in the bio-refining process., with the studied biomass feedstock BTD per truckload representing between 0.89 and 2.88 times the US perimeter.
In this report Lagrangian analysis of materially conserved scalars is applied to the problem of turbulent transport in variable-density flows. The consequences of an additional material conserved quantity, the density, is generally not acknowledged and leads to significant and meaningfully different expressions for turbulent transport in the moment equations. The formal Lagrangian analysis produces gradient transport expressions substantially different from those obtained by the physically intuitive “argument by analogy” method used in computational models. Various intuitive arguments, in Favre and Reynolds averaged settings, are contrasted to the formal Lagrangian results. Using expressions from the formal analysis, we derive consistent gradient transport closures for the turbulent transport terms that appear in the first- and second-order Favre moment equations. Results for coupled multispecies turbulent transport are given. The analysis is limited to variable-density turbulence in which the dilatation of the fluctuating velocity is small. The results are applicable to turbulent combustion and to stellar convection problems in which the density fluctuations are on the order of the mean density.