Generalisable long COVID subtypes: findings from the NIH N3C and RECOVER programmes
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59 BASIC BIOLOGICAL SCIENCES↗
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Results for “Precision Machining”
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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Capturing dynamical correlations using implicit neural representations
Abstract Understanding the nature and origin of collective excitations in materials is of fundamental importance for unraveling the underlying physics of a many-body system. Excitation spectra are usually obtained by measuring the dynamical structure factor, S ( Q , ω ), using inelastic neutron or x-ray scattering techniques and are analyzed by comparing the experimental results against calculated predictions. We introduce a data-driven analysis tool which leverages ‘neural implicit representations’ that are specifically tailored for handling spectrographic measurements and are able to efficiently obtain unknown parameters from experimental data via automatic differentiation. In this work, we employ linear spin wave theory simulations to train a machine learning platform, enabling precise exchange parameter extraction from inelastic neutron scattering data on the square-lattice spin-1 antiferromagnet La 2 NiO 4 , showcasing a viable pathway towards automatic refinement of advanced models for ordered magnetic systems.
36 MATERIALS SCIENCE↗
Toward fully automated UED operation using two-stage machine learning model
To demonstrate the feasibility of automating UED operation and diagnosing the machine performance in real time, a two-stage machine learning (ML) model based on self-consistent start-to-end simulations has been implemented. This model will not only provide the machine parameters with adequate precision, toward the full automation of the UED instrument, but also make real-time electron beam information available as single-shot nondestructive diagnostics. Furthermore, based on a deep understanding of the root connection between the electron beam properties and the features of Bragg-diffraction patterns, we have applied the hidden symmetry as model constraints, successfully improving the accuracy of energy spread prediction by a factor of five and making the beam divergence prediction two times faster. The capability enabled by the global optimization via ML provides us with better opportunities for discoveries using near-parallel, bright, and ultrafast electron beams for single-shot imaging. It also enables directly visualizing the dynamics of defects and nanostructured materials, which is impossible using present electron-beam technologies.
36 MATERIALS SCIENCE↗
Three-flavor collective neutrino oscillation simulations on a qubit quantum annealer
Neutrinos are unique among elementary particles in that their flavor-compositions oscillate over time. In extreme environments such as core-collapse supernovae, neutron-star mergers, and the early Universe, neutrinos are dense enough that their self-interactions significantly affect, if not dominate, these oscillations. This has implications for several phenomena within these environments, particularly nucleosynthesis. Simulations of these self-interactions have traditionally approximated neutrinos as having two flavors instead of the physical three. In order to develop techniques for characterizing the resulting quantum entanglement, I present the results of simulations of neutrino-neutrino interactions that include all three physical neutrino flavors and were performed on D-Wave Inc.’s Advantage 5000+ qubit quantum annealer. These results are checked against those from exact classical simulations, which are also used to compare the neutrino-neutrino interactions to neutrino-antineutrino and interactions between Majorana neutrinos, which are their own antiparticles. The D-Wave Advantage annealer is shown to be able to reproduce time evolution with the precision of a classical machine for small numbers of neutrinos and to do so without the Trotter errors present in most simulations of dynamics on quantum devices. Furthermore, it suffers from poor scaling in qubit-count with the number of neutrinos.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Discreteness noise versus force errors in N-body simulations
A low accuracy in the force calculation per time step of a few percent for each particle pair is sufficient for collisionless N-body simulations. Higher accuracy is made meaningless by the dominant discreteness noise in the form of two-body relaxation, which can be reduced only by increasing the number of particles. Since an N-body simulation is a Monte Carlo procedure in which each particle-particle force is essentially random, i.e., carries an error of about 1000 percent, the only requirement is a systematic averaging-out of these intrinsic errors. We illustrate these assertions with two specific examples in which individual pairwise forces are deliberately allowed to carry significant errors: tree-codes on supercomputers and algorithms on special-purpose machines with low-precision hardware.
Hernquist, Lars↗
Alternative wavelengths for laser ranging
The following are considered to be necessary to accomplish multicolor laser ranging: the nature of the atmospheric dispersion and absorption, the satellite/lunar/ground retro-array characteristics, and ground/satellite ranging machine performance. The energy balance and jitter budget have to be considered as well. It is concluded that the existing satellite/laser retroreflectors seem inadequate for future experiments. The Raman Stokes/Anti-Stokes (0.68/0.43 micron) plus solid state detector appear to be promising instrumentation that satisfy the ground/satellite and satellite/ground ranging machine requirements on the precision, compactness, and data processing.
Hamal, Karel↗
Laser Material Processing for Microengineering Applications
The processing of materials via laser irradiation is presented in a brief survey. Various techniques currently used in laser processing are outlined and the significance to the development of space qualified microinstrumentation are identified. In general the laser processing technique permits the transferring of patterns (i.e. lithography), machining (i.e. with nanometer precision), material deposition (e.g., metals, dielectrics), the removal of contaminants/debris/passivation layers and the ability to provide process control through spectroscopy.
Helvajian, H.↗
Automated Serial Sectioning for 3D Reconstruction
Some aspects of an apparatus and method for automated serial sectioning of a specimen of a solder, aluminum, or other relatively soft opaque material are discussed. The apparatus includes a small milling machine (micromiller) that takes precise, shallow cuts (increments of depth as small as 1 micron) to expose successive sections. A microscope equipped with an electronic camera, mounted in a fixed position on the micromiller, takes pictures of the newly exposed specimen surface at each increment of depth. The images are digitized, and the resulting data are subsequently processed to reconstruct three-dimensional (3D) features of the specimen.
Alkemper, Jen↗
Platform for multi-modal, multi-scale data integration for sustainable agriculture
Explore the source record for details and available documents.
54 ENVIRONMENTAL SCIENCES↗
Positron Sources for Future High Energy Physics Colliders
An unprecedented positron average current is required to fit the luminosity demands of future $e^+e^-$ high energy physics colliders. In addition, in order to access precision-frontier physics, these machines require positron polarization to enable exploring the polarization dependence in many HEP processes cross sections, reducing backgrounds and extending the reach of chiral physics studies beyond the standard model. The ILC has a mature plan for the polarized positron source based on conversion in a thin target of circularly polarized gammas generated by passing the main high energy e-beam in a long superconducting helical undulator. Compact colliders (CLIC, C3 and advanced accelerator-based concepts) adopt a simplified approach and currently do not plan to use polarized positrons in their baseline design, but could greatly benefit from the development of compact alternative solutions to polarized positron production. Increasing the positron current, the polarization purity and simplifying the engineering design are all opportunities where advances in accelerator technology have the potential to make a significant impact. This white-paper describes the current status of the field and provides R&D short-term and long-term pathways for polarized positron sources.
43 PARTICLE ACCELERATORS↗
Precision Polishing of Ablator Capsules via in situ Process Monitoring and Machine Learning–Based Optimization
In inertial confinement fusion (ICF) experiments seeking output gains of unity and beyond, the quality of the ablator capsule is paramount for minimizing the hydrodynamic mix that quenches the central hot spot. Defects in the form of foreign particles or missing mass on the surface and within the wall of the capsule are primary offenders. High-density carbon capsules made for ICF experiments at the National Ignition Facility are precision polished to achieve surface smoothness on the order of a few nanometers as well as to minimize isolated defects in the form of pits. Given the critical role of this process, we are developing smart manufacturing techniques with the goal of elevating the efficiency of this process. Our approach is to use MEMS (micro-electromechanical systems)–based sensors to capture the fine vibration signals generated during the polishing process and combine them with synchronized visual feedback as needed. Beyond using these sensors for process monitoring, we use specific deep learning methods to analyze the data and extract correlations with both the process parameters and the final performance of the polishing run. Here, in this work, we describe the multiple fronts we have explored in this regard and the results we have gotten so far. This approach promises to have the potential to ultimately provide real-time feedback that can be used to ensure the progress of the run as well as a means for faster optimization.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
A Boltzmann machine for the organization of intelligent machines
In the present technological society, there is a major need to build machines that would execute intelligent tasks operating in uncertain environments with minimum interaction with a human operator. Although some designers have built smart robots, utilizing heuristic ideas, there is no systematic approach to design such machines in an engineering manner. Recently, cross-disciplinary research from the fields of computers, systems AI and information theory has served to set the foundations of the emerging area of the design of intelligent machines. Since 1977 Saridis has been developing an approach, defined as Hierarchical Intelligent Control, designed to organize, coordinate and execute anthropomorphic tasks by a machine with minimum interaction with a human operator. This approach utilizes analytical (probabilistic) models to describe and control the various functions of the intelligent machine structured by the intuitively defined principle of Increasing Precision with Decreasing Intelligence (IPDI) (Saridis 1979). This principle, even though resembles the managerial structure of organizational systems (Levis 1988), has been derived on an analytic basis by Saridis (1988). The purpose is to derive analytically a Boltzmann machine suitable for optimal connection of nodes in a neural net (Fahlman, Hinton, Sejnowski, 1985). Then this machine will serve to search for the optimal design of the organization level of an intelligent machine. In order to accomplish this, some mathematical theory of the intelligent machines will be first outlined. Then some definitions of the variables associated with the principle, like machine intelligence, machine knowledge, and precision will be made (Saridis, Valavanis 1988). Then a procedure to establish the Boltzmann machine on an analytic basis will be presented and illustrated by an example in designing the organization level of an Intelligent Machine. A new search technique, the Modified Genetic Algorithm, is presented and proved to converge to the minimum of a cost function. Finally, simulations will show the effectiveness of a variety of search techniques for the intelligent machine.
Moed, Michael C.↗
Precision Polishing of Spheres Via In-Situ Process Monitoring and Machine-Learning-Based Optimization
In inertial confinement fusion (ICF) experiments seeking output gains of unity and beyond, the quality of the ablator capsule is paramount for minimizing hydrodynamic mix that quenches the central hot spot. Defects in the form of foreign particles or missing mass on the surface and within the wall of the capsule are primary offenders. High density carbon capsules made for ICF experiments on the National Ignition Facility (NIF) are precision polished to achieve the surface smoothness in the order of a few nm as well as to minimize isolated defects in the form of pits. Given the critical role of this process, we are developing smart manufacturing techniques with goal of elevating the efficiency of this process. Our approach is to use MEMS-based sensors to capture the fine vibrational signals generated during the polishing process and combine it with synchronized visual feedback as needed. Beyond using these sensors for process monitoring, we use specific deep learning methods to analyze the data and extract correlations with both the process parameters and the final performance of the polishing run. Here, we describe the multiple fronts that we have explored in this regard and the results we have gotten so far. This approach promises to have the potential to ultimately provide real-time feedback that can be used for ensuring the progress of the run as well as a means for faster optimization.
36 MATERIALS SCIENCE↗
Prompt and Precise Prototyping
For Sanders Design International, Inc., of Wilton, New Hampshire, every passing second between the concept and realization of a product is essential to succeed in the rapid prototyping industry where amongst heavy competition, faster time-to-market means more business. To separate itself from its rivals, Sanders Design aligned with NASA's Marshall Space Flight Center to develop what it considers to be the most accurate rapid prototyping machine for fabrication of extremely precise tooling prototypes. The company's Rapid ToolMaker System has revolutionized production of high quality, small-to-medium sized prototype patterns and tooling molds with an exactness that surpasses that of computer numerically-controlled (CNC) machining devices. Created with funding and support from Marshall under a Small Business Innovation Research (SBIR) contract, the Rapid ToolMaker is a dual-use technology with applications in both commercial and military aerospace fields. The advanced technology provides cost savings in the design and manufacturing of automotive, electronic, and medical parts, as well as in other areas of consumer interest, such as jewelry and toys. For aerospace applications, the Rapid ToolMaker enables fabrication of high-quality turbine and compressor blades for jet engines on unmanned air vehicles, aircraft, and missiles.
Source record↗
Machine Vision for Autonomous Small Body Navigation
This paper describes machine vision algorithms that enable precision guidance and hazard avoidance during small body exploration through onboard visual feature tracking and landmark recognition.
Estimation Landmark Recognition↗
Calibration For On-Machine Inspections
Permanent calibration setup on numerically-controlled machine tool enables fast and reliable calibration of automated probes for inspection of workpieces while still mounted on machine. Setup includes one or more artifacts, dimensions and locations known precisely and stored in memory of computer controlling machine. Before probes used to inspect newly machined part, used to check artifacts. Probe measurements compared with values in memory to determine whether probe readings need adjustment.
Haymaker, Carlton L., Jr.↗
Machine-Learning-Driven, Site-Specific Weather Forecasting for Grid-Interactive Efficient Buildings: Preprint
Emerging grid-interactive efficient buildings (GEBs) have great potential to provide much-needed demand flexibility to electric grids while fulfilling their own control targets by co-optimizing smart appliances, solar photovoltaics, electric vehicles, and energy storage at buildings. To enable the optimal operation of GEBs, site-specific weather information—such as temperature, solar irradiance, relative humidity, and wind speed—is crucial; however, this information is generally unavailable or expensive to obtain. This paper develops advanced machine learning methods to provide precise weather forecasts for individual building sites using readily available weather station data. Support vector regression and artificial neural networks have been employed to learn the spatiotemporal correlations between the weather conditions at nearby weather stations and the individual building site. The proposed site-specific weather forecasting methods have been validated using 1-year actual weather measurement data collected in the Denver metro area. Results show that the developed machine-learning-driven methods can accurately forecast the temperature at the target building site 1 hour ahead with mean absolute error less than 0.72°C and a 48% improvement over the persistence method. Site-specific weather forecasts will improve the understanding of the microclimate effect and its impact on building energy consumption. This information will drive efficiency upgrades and adjustments of building control strategies to improve energy savings and increase flexibility in building loads.
30 DIRECT ENERGY CONVERSION↗
Grinding Parts For Automatic Welding
Rollers guide grinding tool along prospective welding path. Skatelike fixture holds rotary grinder or file for machining large-diameter rings or ring segments in preparation for welding. Operator grasps handles to push rolling fixture along part. Rollers maintain precise dimensional relationship so grinding wheel cuts precise depth. Fixture-mounted grinder machines surface to quality sufficient for automatic welding; manual welding with attendant variations and distortion not necessary. Developed to enable automatic welding of parts, manual welding of which resulted in weld bead permeated with microscopic fissures.
Burley, Richard K.↗