Applied mechanics and space research.
Space research and effect on other branches of science, especially applied mechanics
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Space research and effect on other branches of science, especially applied mechanics
We report the application of the new elimination of Rutherford elastic scattering technique for the measurement of proton-induced reaction cross sections utilizing stored ions decelerated to astrophysical energies. This approach results in a background reduction factor of about 1 order of magnitude, enabling the first measurement of a (p, n) cross section in a storage ring. Here, the reaction channels 124 Xe(p,n) and 124 Xe(p,γ) have been studied just above the neutron threshold energy. The new data provide valuable constraints for Hauser-Feshbach theory and extrapolation of the (p,γ) cross section to lower energies. Most importantly, for nuclei of limited availability, the method represents a powerful improvement to efficiently study proton-induced reactions at energies within or close to the astrophysical Gamow window, bringing many reaction measurements within reach that were previously inaccessible in the laboratory.
The Fast Beam Condition Monitor (FBCM) is a standalone luminometer for the High Luminosity LHC (HL-LHC) program of the CMS Experiment at CERN. The detector is under development and features a new, radiation-hard, front-end application-specific integrated circuit (ASIC) designed for beam monitoring applications. The achieved timing resolution of a few nanoseconds enables the measurement of both the luminosity and the beam-induced background. The ASIC, called FBCM23, features six channels with adjustable shaping times, enabling in-field fine-tuning. Each ASIC channel outputs a single binary asynchronous signal encoding time-of-arrival and time-over-threshold information. The FBCM is based on silicon-pad sensors, with two sensor designs presently being considered. This paper presents the results of tests of the FBCM detector prototype using both types of silicon sensors with hadron, muon, and electron beams. Irradiated FBCM23 ASICs and silicon-pad sensors were also tested to simulate the expected conditions near the end of the detector's lifetime in the HL-LHC radiation environment. Based on test results, direct bonding between the sensor and ASIC was chosen, and an optimal bias voltage and ASIC threshold for FBCM operation were proposed. The current design of the front-end test board was validated following the beam test and is now being used for the first front-end module, which is expected to be produced in summer 2025. These results represent a major step forward in validating the FBCM concept, first version of the firmware and establishing a reliable design path for the final detector.
Graph and network theory play a fundamental role in quantum computer sciences, including quantum information and computation. Random graphs and complex network theory are pivotal in predicting novel quantum phenomena, where entangled links are represented by edges. Quantum algorithms have been developed to enhance solutions for various network problems, giving rise to quantum graph computing and quantum graph learning (QGL). Here, in this review, we explore graph theory and graph learning methods as powerful tools for quantum computers to generate efficient solutions to problems beyond the reach of classical systems. We delve into the development of quantum complex network theory and its applications in quantum computation, materials discovery, and research. We also discuss quantum machine learning (QML) methodologies for effective image classification using qubits, quantum gates, and quantum circuits. Additionally, the paper addresses the challenges of QGL and algorithms, emphasizing the steps needed to develop flexible QGL solvers. This review presents a comprehensive overview of the fields of QGL and QML, highlights recent advancements, and identifies opportunities for future research.
Technology assessments of fourteen science instruments were conducted within NASA using the NASA Technology Readiness Level (TRL) Metric. The instruments were part of three NASA Earth Science Decadal Survey missions in pre-formulation. The Earth Systematic Missions Program (ESMP) Systems Engineering Working Group (SEWG), composed of members of three NASA Centers, provided a newly modified electronic workbook to be completed, with instructions. Each instrument development team performed an internal assessment of its technology status, prepared an overview of its instrument, and completed the workbook with the results of its assessment. A team from the ESMP SEWG met with each instrument team and provided feedback. The instrument teams then reported through the Program Scientist for their respective missions to NASA's Earth Science Division (ESD) on technology readiness, taking the SEWG input into account. The instruments were found to have a range of TRL from 4 to 7. Lessons Learned are presented; however, due to the competition-sensitive nature of the assessments, the results for specific missions are not presented. The assessments were generally successful, and produced useful results for the agency. The SEWG team identified a number of potential improvements to the process. Particular focus was on ensuring traceability to guiding NASA documents, including the NASA Systems Engineering Handbook. The TRL Workbook has been substantially modified, and the revised workbook is described.
The NASA Physical Sciences Informatics (PSI) database is NASA’s archival for physical sciences research in microgravity – on ISS and also other reduced gravity platforms. The database has been making data from microgravity physical science investigations publicly available since its launch late 2014. The database was an early investment in Open Science for NASA’s Biophysics and Physical Sciences (BPS) Division of the Science Mission Directorate (SMD), who conducts fundamental and applied physical sciences yielding research data in 6 disciplines: biophysics, combustion science, complex fluids, fluid physics, fundamental physics, and materials science. PSI started initially with data from 14 microgravity investigations. Receipt of data through the years and an annual NRA to fund ground investigations extending flight datasets has increased the total to 72 investigations available with 8 new datasets in the 2020 NRA (NNH20ZDA014N). These new datasets are open for public access at the PSI website at https://www.nasa.gov/PSI.
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This report summarizes research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, fluid mechanics, and computer science during the period October 1, 1993 through March 31, 1994. The major categories of the current ICASE research program are: (1) applied and numerical mathematics, including numerical analysis and algorithm development; (2) theoretical and computational research in fluid mechanics in selected areas of interest to LaRC, including acoustics and combustion; (3) experimental research in transition and turbulence and aerodynamics involving LaRC facilities and scientists; and (4) computer science.
This paper describes an experiment to prototype a new way of conducting science by applying networking and distributed computing technologies to an Earth Science application. A combination of satellite, wireless, and terrestrial networking provided geologists at a remote field site with interactive access to supercomputer facilities at two NASA centers, thus enabling them to validate and calibrate remotely sensed geological data in near-real time. This represents a fundamental shift in the way that Earth scientists analyze remotely sensed data. In this paper we describe the experiment and the network infrastructure that enabled it, analyze the data flow during the experiment, and discuss the scientific impact of the results.
Overview of OCIO's methodology for applying data science in aerospace domains.
Abstract Diversity of the naive T cell repertoire is maintained by competition for stimuli provided by self-peptides bound to major histocompatibility complexes (self-pMHCs). We extend an existing bi-variate competition model to a multi-variate model of the dynamics of multiple T cell clonotypes which share stimuli. In order to understand the late-time behaviour of the system, we analyse: (i) the dynamics until the extinction of the first clonotype, (ii) the time to the first extinction event, (iii) the probability of extinction of each clonotype, and (iv) the size of the surviving clonotypes when the first extinction event takes place. We also find the probability distribution of the number of cell divisions per clonotype before its extinction. The mean size of a new clonotype at quasi-steady state is an increasing function of the stimulus available to it, and a decreasing function of the fraction of stimuli it shares with other clonotypes. Thus, the probability of, and time to, extinction of a new clonotype entering the pool of T cell clonotypes is determined by the extent of competition for stimuli it experiences and by its initial number of cells.
Abstract Noncanonical cofactor biomimetics (NCBs) such as nicotinamide mononucleotide (NMN + ) provide enhanced scalability for biomanufacturing. However, engineering enzymes to accept NCBs is difficult. Here, we establish a growth selection platform to evolve enzymes to utilize NMN + -based reducing power. This is based on an orthogonal, NMN + -dependent glycolytic pathway in Escherichia coli which can be coupled to any reciprocal enzyme to recycle the ensuing reduced NMN + . With a throughput of >10 6 variants per iteration, the growth selection discovers a Lactobacillus pentosus NADH oxidase variant with ~10-fold increase in NMNH catalytic efficiency and enhanced activity for other NCBs. Molecular modeling and experimental validation suggest that instead of directly contacting NCBs, the mutations optimize the enzyme’s global conformational dynamics to resemble the WT with the native cofactor bound. Restoring the enzyme’s access to catalytically competent conformation states via deep navigation of protein sequence space with high-throughput evolution provides a universal route to engineer NCB-dependent enzymes.
Abstract Potassium dihydrogen phosphate (KDP) and its deuterated analog (DKDP) are unique nonlinear optical materials for high power laser systems. They are used widely for frequency conversion and polarization control by virtue of the ability to grow optical-quality crystals at apertures suitable for fusion-class laser systems. Existing methods for freeform figuring of KDP/DKDP optics do not produce surfaces with sufficient laser-induced–damage thresholds (LIDT’s) for operation in the ultraviolet portion of high-peak-power laser systems. In this work, we investigate fluid jet polishing (FJP) using a nonaqueous slurry as a sub-aperture finishing method for producing freeform KDP surfaces. This method was used to selectively polish surface areas to different depths on the same substrate with removals ranging from 0.16 μm to 5.13 μm. The finished surfaces demonstrated a slight increase in roughness as the removal depth increased along with a small number of fracture pits. Laser damage testing with 351 nm, 1 ns pulses demonstrated excellent surface damage thresholds, with the highest values in areas devoid of fracture pits. This work demonstrates, for the first time, a method that enables fabrication of a waveplate that provides tailored polarization randomization that can be scaled to meter-sized optics. Furthermore, this method is based on FJP technology that incorporates a nonaqueous slurry specially designed for use with KDP. This novel nonaqueous FJP process can be also used for figuring other types of materials that exhibit similar challenging inherent properties such as softness, brittleness, water-solubility, and temperature sensitivity.
The PHENIX experiment measured the centrality dependence of two-pion Bose-Einstein correlation functions in $\sqrt{𝑠{𝑁𝑁}}$ = 200 GeV Au + Au collisions at the Relativistic Heavy Ion Collider at Brookhaven National Laboratory. The data are well represented by Lévy-stable source distributions. The extracted source parameters are the correlation-strength parameter 𝜆, the Lévy index of stability 𝛼, and the Lévy-scale parameter 𝑅 as a function of transverse mass 𝑚 𝑇 and centrality. The 𝜆(𝑚 𝑇 ) parameter is constant at larger values of 𝑚 𝑇 , but decreases as 𝑚 𝑇 decreases. The Lévy-scale parameter 𝑅(𝑚 𝑇 ) decreases with 𝑚 𝑇 and exhibits proportionality to the length scale of the nuclear overlap region. The Lévy exponent 𝛼(𝑚 𝑇 ) is independent of 𝑚 𝑇 within uncertainties in each investigated centrality bin, but shows a clear centrality dependence. At all centralities, the Lévy exponent 𝛼 is significantly different from that of Gaussian (𝛼 = 2) or Cauchy (𝛼 = 1) source distributions. Comparisons to the predictions of Monte-Carlo simulations of resonance-decay chains show that, in all but the most peripheral centrality class (50%–60%), the obtained results are inconsistent with the measurements, unless a significant reduction of the in-medium mass of the 𝜂′ meson is included. Finally, in each centrality class, the best value of the in-medium 𝜂′ mass is compared to the mass of the 𝜂 meson, as well as to several theoretical predictions that consider restoration of U 𝐴 (1) symmetry in hot hadronic matter.
Heterogeneous nucleation from defects dominates the electric field required for polarization switching of ferroelectrics. Here, we consider the switching of a nominally non-switchable polar thin film of AlN due to the proximity effect arising from embedded ferroelectric nanoclusters of Al 1-x Sc x N. Using a Landau-Ginzburg-Devonshire thermodynamic approach and finite element modeling, we study the influence of nanocluster shape on polarization switching and domain nucleation emerging in AlN. The ferroelectric nanocluster boundary is modeled as a thin layer transitioning from Al 1-x Sc x N to AlN. We analyze the conditions under which polarization switching in the AlN film occurs at coercive fields significantly lower than its dielectric breakdown field. In the presence of spike-like Al 1-x Sc x N nanoclusters, the proximity effect enables switching of the spontaneous polarization in AlN and significantly reduces the corresponding coercive field. The internal field, which is depolarizing inside the AlN (due to its larger spontaneous polarization) and polarizing within the ferroelectric Al 1-x Sc x N nanoclusters (due to its smaller spontaneous polarization), lowers the potential barrier in the clusters and nucleates nanodomains at the Al 1-x Sc x N-AlN interface, forming localized regions of reversed polarization. Proximity effect can thus provide a pathway towards "thawing" previously "frozen" ferroelectrics through engineered nucleation for memory, actuation and optical technologies.
This report summarizes research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, computer science, fluid mechanics, and structures and materials during the period October 1, 1999 through March 31, 2000.
Abstract Dissolved organic carbon (DOC) in coastal waters is integral to biogeochemical cycling, but global and regional drivers of DOC are still uncertain. In this study we explored spatial and temporal differences in DOC concentrations and stocks across the global coastal ocean, and how these relate to temperature and salinity. We estimated a global median coastal DOC stock of 3.15 Pg C (interquartile range (IQR) = 0.85 Pg C), with median DOC concentrations being 2.2 times higher than in open ocean surface waters. Globally and seasonally, salinity was the main driver of DOC with concentrations correlated negatively with salinity, without a clear relationship to temperature. DOC concentrations and stocks varied with region and season and this pattern is likely driven by riverine inputs of DOC and nutrients that stimulate coastal phytoplankton production. Temporally, high DOC concentrations occurred mainly in months with high freshwater input, with some exceptions such as in Eastern Boundary Current margins where peaks are related to primary production stimulated by nutrients upwelled from the adjacent ocean. No spatial trend between DOC and temperature was apparent, but many regions (19 out of 25) had aligned peaks of seasonal temperature and DOC, related to increased phytoplankton production and vertical stratification at high temperatures. Links of coastal DOC with salinity and temperature highlight the potential for anthropogenic impacts to alter coastal DOC concentration and composition, and thereby ecosystem status.