Burkhardt-Cottingham-type sum rules for light-cone and quasi-PDFs
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Using ( 10 087 ± 44 ) × 10 6 J / ψ events collected with the BESIII detector, numerous Ξ − and Λ decay asymmetry parameters are simultaneously determined from the process J / ψ → Ξ − Ξ ¯ + → Λ ( p π − ) π − Λ ¯ ( n ¯ π 0 ) π + and its charge-conjugate channel. The precisions of α Λ 0 for Λ → n π 0 and α ¯ Λ 0 for Λ ¯ → n ¯ π 0 compared to world averages are improved by factors of 4 and 1.7, respectively. The ratio of decay asymmetry parameters of Λ → n π 0 to that of Λ → p π − , ⟨ α Λ 0 ⟩ / ⟨ α Λ − ⟩ , is determined to be 0.873 ± 0.01 2 − 0.010 + 0.011 , where the first and the second uncertainties are statistical and systematic, respectively. The ratio is smaller than unity more than 5 σ , which signifies the existence of the Δ I = 3 / 2 transition in Λ for the first time. Besides, we test for C P symmetry in Ξ − → Λ π − and in Λ → n π 0 with the best precision to date. Published by the American Physical Society 2024
Mechanical properties of disordered networks can be significantly tailored by modifying a small fraction of their bonds. This procedure has been used to design and build mechanical metamaterials with a variety of responses. A long-range “allosteric” response, where a localized input strain at one site gives rise to a localized output strain at a distant site, has been of particular interest. This work presents an approach to incorporating allosteric responses in experimental systems by pruning disordered networks in situ. Previous work has relied on computer simulations to design and predict the response of such systems using a cost function where the response of the entire network to each bond removal is used at each step to determine which bond to prune. It is not feasible to follow such a design protocol in experiments where one has access only to local response at each site. This paper presents design algorithms that allow determination of what bonds to prune based purely on the local forces in the network without employing a cost function; using only local information, allosteric networks are designed in simulations and then built out of real materials. The results show that some pruning strategies work better than others when translated into an experimental system. A method is presented to measure local stresses experimentally in disordered networks. This approach is then used to implement pruning methods to design desired responses in situ. Results from these experiments confirm that the pruning methods are robust and work in a real laboratory material.
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While much research has been conducted in Human Mobility Science, most studies on the analytics/insights part generally focus on one of the following: processing and analytics on human stop-trip behavior, design of individual mobility metrics (often in silos), calculation and characterization of only a handful (typically 5-6) of human mobility metrics on geospatial-temporal human mobility data of interest. Although human mobility research offers a vast and diverse array of available metrics, most individual studies typically compute only a small subset of five or six metrics at a time when analyzing trajectory datasets of human mobility across different areas of interest. This paper is motivated by the critical need to repeatedly compute an extensive array of human mobility metrics across several trajectory datasets and perform individual metric-level benchmarking to establish a new, standardized Test and Evaluation (T&E) suite for the field of Human Mobility Science. We first present our findings on the minimal yet sufficient pre-processing required to reliably and efficiently compute a wide range of human mobility metrics. The key findings are specifically related to the proposed Composite Stop Locations table, which serves as a core pre-processing data layer. Subsequently, we present a case study demonstrating how the Composite Stop Locations table facilitates computation of at least 14 distinct human mobility metrics (unlike 5-6 different set of metrics used for studies in the literature) using the popular and open-source OpenPFLOW dataset. Finally, we have also presented an example of our benchmarking methodology to evaluate the quality and performance of the trajectory dataset of interest, assessed across multiple human mobility metrics.
Uranium borides are promising candidate fuel forms for use in advanced nuclear reactors due to their high thermal conductivity and potential for dual use as both fuel and burnable absorber. In this work, uranium tetraboride () and uranium monoboroncarbide (UBC) composite were synthesized by using industrially scalable carboborothermic reduction method. The final uranium boride phase composition is sensitive to the sample holding crucibles ( and graphite) such that graphite supply excess carbon, promoting the formation of a predominant UBC phase. The high‐temperature in situ synchrotron X‐ray diffraction of pristine –UBC show persistence , UBC, and phases while preoxidized –UBC leads to predominant and formation due to progressive oxidation and boron loss at high temperature. The oxidation behavior was further characterized using thermogravimetric analysis, allowing direct comparison with other potential accident tolerant fuels such as , , UC, and UN. The –UBC shows higher uranium loading than monolithic and demonstrates promising oxidation behavior at high temperature, pointing to its potential as an improved uranium boride‐based fuel form.
This technical note describes a minimum creep rate model for 2-1/4Cr-1Mo steel that is consistent with the current creep strain equation embedded in the ASME Boiler & Pressure Vessel Code Section III, Division 5, Subsection HB, Subpart B isochronous stress–strain curves. Minimum creep rate models for all the Section III, Division 5 Class A materials are required for the development of improved high temperature design methods. Of all the Class A materials, only 2-1/4Cr-1Mo does not have a readily identifying minimum creep rate term in the current isochronous stress–strain curve model.
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Antibiotic-resistant bacteria rapidly spread in clinical and natural environments and challenge our modern lifestyle. A major component of defense against antibiotics in Gram-negative bacteria is a drug permeation barrier created by active efflux across the outer membrane. We identified molecular determinants defining the propensity of small peptidomimetic molecules to avoid and inhibit efflux pumps in Pseudomonas aeruginosa, a human pathogen notorious for its antibiotic resistance. Combining experimental and computational protocols, we mapped the fate of the compounds from structure-activity relationships through their dynamic behavior in solution, permeation across both the inner and outer membranes, and interaction with MexB, the major efflux transporter of P. aeruginosa. We identified predictors of efflux avoidance and inhibition and demonstrated their power by using a library of traditional antibiotics and compound series and by generating new inhibitors of MexB. The identified predictors will enable the discovery and optimization of antibacterial agents suitable for treatment of P. aeruginosa infections.
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In 1975, Congress passed the Energy Policy and Conservation Act (EPCA), requiring standards for corporate average fuel economy (CAFE), and charging the U.S. Department of Transportation (DOT) with the establishment and enforcement of these standards. The Secretary of Transportation has delegated these responsibilities to the National Highway Traffic Safety Administration (NHTSA). NHTSA has contracted the DOT Volpe National Transportation Systems Center (Volpe Center) to provide analytical support for NHTSA’s regulatory and analytical activities related to fuel economy standards. Unlike long-standing safety and criteria pollutant emissions standards, fuel economy standards apply to manufacturers’ overall fleets rather than to individual vehicle models. In developing the standards, NHTSA made use of the CAFE Compliance and Effects Modeling System (the “CAFE model”), which was developed by DOT’s Volpe Center for the 2005-2007 CAFE rulemaking and has been continually updated since. The model is the primary tool used by the agency to evaluate potential CAFE stringency levels by applying technologies incrementally to each manufacturer’s fleet until the requirements under consideration are met. The CAFE model relies on numerous technology-related and economic inputs such as market forecasts and technology cost and effectiveness estimates; these inputs are categorized by vehicle classification, technology synergies, phase-in rates, cost learning curve adjustments, and technology “decision trees.” The Volpe Center assists NHTSA in the development of the engineering and economic inputs to the CAFE model by analyzing the application of potential technologies to the current automotive industry vehicle fleet to determine the feasibility of future CAFE standards, the associated costs, and the benefits of the standards.
In Mexico, there are various amendments, approved and under discussion to significantly modify the order in which generation units are committed and dispatched. This report quantifies the potential impacts on Mexico's power system, utilizing a production cost model of the Mexican power system that analyzes the hourly optimal electricity dispatch of the Mexican electricity system for 1 year under four scenarios, a reference scenario, and three alternative scenarios. These scenarios are meant to evaluate the potential impacts of increasing participation of the state-owned power plants in generation mix, electricity production costs, emissions, and renewable curtailment.
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