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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Geometric Interpretation of the Cluster Location Problem Part II: Application to the Pahala, Hawaii, Earthquake Sequence

In the companion “Theory” article, we presented a new framing of the seismic location problem in terms of differential geometry (Harris et al., 2025). From that viewpoint, we developed a “project and correct” approach for estimating the relative locations of earthquakes. Here, in this study, we use project and correct to estimate high-precision relative locations of events from an earthquake sequence beneath the town of Pahala, Hawaii, using high-precision correlation-derived picks. The sequence was active from 2020 through 2022 and produced many highly correlated signals at Hawaii Volcano Observatory (HVO) stations on the island of Hawaii. The data we inverted consisted of 2882 events with observations at 5 HVO stations. For comparison with the travel-time image, we also produced conventional hypocenter solutions using both the Bayesloc program (Myers et al., 2007, 2009) and a purpose-built double-difference code. There were obvious structural elements in the resulting image, the resolution of which we used to test the performance of the project and the correct algorithm. For the projection step, we first produced a 3D local basis using an singular value decomposition (SVD) of the 2882 groups of times. Projection of the travel-time vectors into this basis resulted in an image with structures similar to those produced by our conventional locators, but with distortion as predicted by theory. Removing the distortion requires an inverse operator generated from the metric tensor at the geometric centroid of the events. We compared two approaches to obtaining such an inverse operator. The first uses an estimate of the geographic centroid of the event cloud from the centroid of the travel-time data. The second approach uses the centroid of the conventionally produced locations. The first approach produces a corrected image very similar to the conventional results, but with a rotation. The corrected image produced using the conventionally derived centroid is a near-exact match to the conventional locations.

Dodge, Douglas A. [Lawrence Livermore National Lab↗
DOE OSTI2026

Emerging anomaly detection techniques for electronic health records: A survey

Background Anomaly detection in electronic health records (EHRs) is a cornerstone of biomedical informatics, with direct implications for patient safety, clinical decision-making, and the prevention of healthcare fraud. Once guided primarily by simple rule-based methods, the field has advanced rapidly, driven by increased computing power, richer and more detailed health data, and the rise of machine learning and deep learning techniques. The objective of this paper is to provide a comprehensive overview of modern approaches to detecting anomalies in EHRs, outlining their strengths, limitations, and relevance to key healthcare challenges. We review traditional statistical methods alongside newer ML- and DL-based strategies and hybrid models, with particular attention to how these techniques support transparency and build clinical trust. Methods This paper presents a thorough and critical survey through systematic review (PRISMA-based) of the latest anomaly detection strategies in time-sequence data domains within electronic health record systems. Results We explore a broad spectrum of methodologies, including statistical models, supervised and unsupervised learning approaches, hybrid frameworks, and state-of-the-art ML-based techniques that collectively advance the precision and scalability of detecting anomalies in complex clinical datasets. In addition to mapping current capabilities, we address the enduring challenges that hinder widespread implementation and provide a forward-looking perspective on the future of anomaly detection in the data-rich landscape of modern healthcare. Summary The advancement in AI-based approaches is reported along with the basic principles of the individual approaches and their applicability. The increased availability of high-quality data, advancements in DL approaches, and enhanced computation power are leading to more frequent adaptation of DL-based approaches. Emerging DL-based approaches that have been adapted in other domains or recently applied in the EHR domain are also discussed in detail. Although DL-based approaches can improve model predictions by incorporating comorbidities, their application is limited in low-frequency data domains (e.g., when the total available data remains in the single digits). Therefore, the user must carefully consider the application based on data availability.

Anomaly detection↗
DOE OSTI2022

Cyber-Attack Identification of Synchrophasor Data Via VMD and Multifusion SVM

A large amount of synchrophasor data in the wide area measurement system (WAMS) needs to be collected and transmitted to the phasor data concentrator, thereby increasing the possibility of being attacked by hackers. The attacked data are therefore hidden into the normal synchrophasor data so that the synchrophasor data based application will be affected. To remedy this problem, an identification framework is proposed to detect the data cyber-attack in WAMS utilizing variational mode decomposition (VMD) and multifusion support vector machine (MSVM). First, VMD is used to transform the attacked data into multiple modal components. Thereafter, a novel MSVM is employed to classify the deterministic features using the proposed linear combined multikernel (LCM). Further, this LCM can fuse multiple types of features, including the time, frequency, and statistical domains of the synchrophasor data. Utilizing the actual data from FNET/GridEye, different experiments are conducted under multiple attack strengths and types. The results demonstrate that the identification framework has higher precision and robustness compared with other conventional classifiers.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1989

Domain decomposition methods for systems of conservation laws: Spectral collocation approximations

Hyperbolic systems of conversation laws are considered which are discretized in space by spectral collocation methods and advanced in time by finite difference schemes. At any time-level a domain deposition method based on an iteration by subdomain procedure was introduced yielding at each step a sequence of independent subproblems (one for each subdomain) that can be solved simultaneously. The method is set for a general nonlinear problem in several space variables. The convergence analysis, however, is carried out only for a linear one-dimensional system with continuous solutions. A precise form of the error reduction factor at each iteration is derived. Although the method is applied here to the case of spectral collocation approximation only, the idea is fairly general and can be used in a different context as well. For instance, its application to space discretization by finite differences is straight forward.

Quarteroni, Alfio↗
NASA NTRS1992

Extended abstract: Managing disjunction for practical temporal reasoning

One of the problems that must be dealt with in either a formal or implemented temporal reasoning system is the ambiguity arising from uncertain information. Lack of precise information about when events happen leads to uncertainty regarding the effects of those events. Incomplete information and nonmonotonic inference lead to situations where there is more than one set of possible inferences, even when there is no temporal uncertainty at all. In an implemented system, this ambiguity is a computational problem as well as a semantic one. In this paper, we discuss some of the sources of this ambiguity, which we will treat as explicit disjunction, in the sense that ambiguous information can be interpreted as defining a set of possible inferences. We describe the application of three techniques for managing disjunction in an implementation of Dean's Time Map Manager. Briefly, the disjunction is either: removed by limiting the expressive power of the system, or approximated by a weaker form of representation that subsumes the disjunction. We use a combination of these methods to implement an expressive and efficient temporal reasoning engine that performs sound inference in accordance with a well-defined formal semantics.

Boddy, Mark↗
NASA NTRS1997

Novel Highly Parallel and Systolic Architectures Using Quantum Dot-Based Hardware

VLSI technology has made possible the integration of massive number of components (processors, memory, etc.) into a single chip. In VLSI design, memory and processing power are relatively cheap and the main emphasis of the design is on reducing the overall interconnection complexity since data routing costs dominate the power, time, and area required to implement a computation. Communication is costly because wires occupy the most space on a circuit and it can also degrade clock time. In fact, much of the complexity (and hence the cost) of VLSI design results from minimization of data routing. The main difficulty in VLSI routing is due to the fact that crossing of the lines carrying data, instruction, control, etc. is not possible in a plane. Thus, in order to meet this constraint, the VLSI design aims at keeping the architecture highly regular with local and short interconnection. As a result, while the high level of integration has opened the way for massively parallel computation, practical and full exploitation of such a capability in many applications of interest has been hindered by the constraints on interconnection pattern. More precisely. the use of only localized communication significantly simplifies the design of interconnection architecture but at the expense of somewhat restricted class of applications. For example, there are currently commercially available products integrating; hundreds of simple processor elements within a single chip. However, the lack of adequate interconnection pattern among these processing elements make them inefficient for exploiting a large degree of parallelism in many applications.

Fijany, Amir↗
NASA NTRS2001

A Step Response Based Mixed-Signal BIST Approach for Continuous-time Linear Circuits

A new Mixed-Signal Built-in self-test approach that is based upon the step response of a reconfigurable (or multifunction) analog block is presented in this paper. The technique requires the overlapping step response of the Circuit Under Test (CUT) for two circuit configurations. Each configuration can be realized by changing the topology of the CUT or by sampling two CUT nodes with differing step responses. The technique can effectively detect both soft and hard faults and does not require an analog-to-digital converter (ADC) and/or digital-to-analog converter(DAC). It also does not require any precision voltage sources or comparators. This approach does not require any additional analog circuits to realize the test signal generator and sample circuits. The paper is concluded with the application of the proposed approach to a circuit found in the work of Epstein et al and two ITC 97 analog benchmark circuits.

Walker, Alvernon↗
DOE OSTI2026

Passive Energy-Saving Solutions for Clothes Dryers: A Modeling and Experimental Study for Improved Efficiency and Affordability

Dryers are integral appliances in modern households, yet their significant power consumption remains a critical challenge for reducing energy bills and upgrades. This work presents the outcomes of a comprehensive investigation aimed at lowering the operating energy costs of the dryer through modeling and experimental approaches. Specifically, the objectives of this research are twofold: (1) to reduce energy consumption without negatively impacting drying performance or time; and (2) to ensure affordability by developing retrofittable solutions characterized by low cost and a quick payback period. These strategies promise universal applicability to all dryer categories, encompassing both gas and electric models, by tackling core issues such as unnecessary heat loss and excess energy supply, both prevalent across dryer designs. Our methodology combines robust modeling frameworks and experimental validation to target energy efficiency improvements through three primary pathways: (1) effective heat loss management using ultralow-cost insulation materials tailored for dryer systems; (2) heat management across the drying cycle, facilitated by passive heat transfer mechanisms, and (3) optimization of heat supply to the load to ensure precise energy delivery, minimizing waste. These innovations are designed to seamlessly integrate with existing dryer configurations, providing a scalable and retrofittable solution that ensures affordability without requiring substantial redesigns or expensive components. Using these methods, the study demonstrates improvement opportunities in dryer energy consumption while maintaining the desired performance. The modeling component utilizes computational simulations to evaluate the thermal and energy performance of these innovations under varied operational conditions, providing foundational insights for experimental design. By addressing critical areas such as heat loss, energy recovery, and supply optimization, this work proposes impactful solutions for lowering the energy costs in domestic clothes dryers. The ultralow-cost, retrofittable nature of the proposed strategies ensures widespread adoption potential across diverse dryer categories, making significant strides toward affordable household energy practices.

Cheekatamarla, Praveen [ORNL] (ORCID:0000000248827↗
DOE OSTI2025

Development of an ERT‐Based Framework for Bentonite Buffers Monitoring From Laboratory Tests: 2. Quantitative Moisture Dynamics Estimation Model

Abstract The long‐term containment of high‐level radioactive waste in geological disposal repositories relies on Engineered Barrier Systems (EBS), with bentonite clay emerging as a candidate material due to its unique properties. Understanding moisture dynamics within bentonite buffers is crucial for EBS performance, as it directly influences the material's swelling capacity, thermal and hydraulic conductivity, mechanical properties, and long‐term evolution under complex thermal‐hydrological‐mechanical (THM) processes. This study develops an advanced Electrical Resistivity Tomography (ERT)‐based framework to quantitatively monitor moisture dynamics under THM conditions. Our framework extends the Waxman‐Smits model to incorporate the coupled effects of temperature, water content, fluid chemistry, and mechanical changes on bentonite's electrical properties. Utilizing HotBENT‐Lab data from our companion paper, which includes electrical conductivity, CT density, and thermocouple measurements, this study offers a novel methodological framework bridging different scales of the model. Our results show that the extended model can estimate water content from ERT data, capturing spatial and temporal variations in moisture distribution within bentonite columns. However, the model tends to overestimate water content compared to CT density‐derived measurements. We address this discrepancy by incorporating a simplified swelling effect model, which improves agreement between ERT and CT density‐based water content estimates. We also discuss model limitations, including simplified treatment of swelling and micropore effects, and propose a conceptual framework for transitioning from laboratory to field applications, addressing challenges such as parameter scalability, field validation methods, and integration of diverse data sources. This ERT‐based framework can potentially advance real‐world moisture monitoring of bentonite‐based EBS in nuclear waste repositories. Plain Language Summary Safely containing high‐level radioactive waste depends on barriers made from materials like bentonite clay, which is effective because it swells and seals in the waste. To ensure these barriers work well over time, it's important to understand how moisture moves through the clay. Our study developed a new method using ERT to monitor moisture levels in bentonite under conditions that mimic those in actual storage sites, including changes in temperature, water content, and mechanical stress. This study improved an existing model to better account for how these factors affect the clay, allowing us to create more accurate moisture maps. Initially, the proposed model overestimated the amount of water in the clay, but its accuracy was improved by factoring in how the clay swells when wet. This study also identified some limitations of the model and suggested ways to adapt it for use in real‐world waste storage sites. This new approach could lead to better monitoring and safety checks for nuclear waste storage systems, helping to ensure long‐term containment. Key Points This work develops an ERT‐based framework extending the Waxman‐Smits model to monitor bentonite moisture dynamics during coupled THM processes The extended model accurately estimates water content from Electrical Resistivity Tomography data, incorporating swelling effects to improve precision This work proposes a conceptual framework for transitioning from laboratory to field applications, advancing EBS monitoring in nuclear waste repositories

Chen, Hang↗
DOE OSTI2026

Comments on the paper “Eliminating beam-induced depolarizing effects in the hydrogen jet target for high-precision proton beam polarimetry at the Electron-Ion Collider” (Part I)

A critical review of the methodology used in F. Rathmann et al., Phys. Rev. Accel. Beams 29, 021001 (2026), to evaluate beam-induced depolarization of the Atomic Polarized Hydrogen Gas Jet (HJET) target at the Electron–Ion Collider (EIC) is presented. It is shown that several key assumptions underlying that analysis—including the introduction of a photon emission threshold, the application of Fermi’s Golden Rule to coherent hyperfine transitions, the interpretation of power broadening as a physical linewidth increase, and the treatment of spatial magnetic fields—are either incorrect or internally inconsistent. As a consequence, the predicted large depolarization effects are demonstrated to be artifacts of the adopted methodology rather than genuine physical phenomena. A consistent quantum-mechanical treatment based on the time-dependent Schrödinger equation shows that beam-induced depolarization probabilities at the EIC are negligibly small.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Immersive Digital Twin Laboratory for Engineering Education (CRADA Final Report)

This project aimed to create an immersive digital twin laboratory that incorporates advanced tracking and visualization capabilities. In collaboration with Fort Lewis College, NREL designed a state-of-the-art physical visualization laboratory, developed a software platform to enable interaction with tracked physical objects in the laboratory, and provided proof-of-concept curricula that included manipulating these tracked objects. The project was initiated to address the growing need for innovative educational tools in engineering education. As renewable energy systems, particularly solar installations, become more complex, there is a pressing need to bridge the gap between theoretical knowledge and practical application. Traditional methods of teaching solar engineering concepts often fall short of providing students with a comprehensive, hands-on understanding. This immersive digital twin laboratory was conceived to fill that gap by creating a safe, non-energized setting where students can interact with augmented solar installation objects, gaining valuable insights into system performance, design, and maintenance. The project utilized extended reality (XR) technologies, including head-mounted displays (HMDs) and a whole-room optical motion tracking system, to connect physical objects with their digital twins in real time. The laboratory was equipped with MagicLeap 2 HMDs, supported by a Vicon Vero 2.2 Optical Tracking System, which provided precise 6-degrees-of-freedom (6-DOF) tracking. We developed a software platform to manage the interaction between the tracked physical objects and their virtual counterparts, enabling real-time data synchronization, object recognition, and virtual overlays. We designed the system to be flexible and extendable, allowing for future integration of additional objects and curriculum. This research advances the field of engineering education by demonstrating the potential of immersive digital twin environments. The laboratory provides a dynamic learning space where students can experiment, collaborate, and learn without the risks associated with live experimentation. The ability to simulate and manipulate solar installation objects under various conditions has broad implications for workforce development, particularly in renewable energy. The project also highlights the economic feasibility of using XR technologies in educational settings, offering a cost-effective solution for institutions looking to enhance their curriculum. By fostering a deeper understanding of solar energy systems, this work contributes to the broader goal of supporting the global energy transition and preparing the next generation of engineers and technicians.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Slitless spectrophotometry with forward modelling: Principles and application to measuring atmospheric transmission

Context.In the next decade, many optical surveys will aim to answer the question of the nature of dark energy by measuring its equation-of-state parameter at the per mill level. This requires trusting the photometric calibration of the survey with a precision never reached so far on many sources of systematic uncertainties. The measurement of the on-site atmospheric transmission for each exposure, or for each season or for the full survey on average, can help reach the per mill precision for the magnitudes. Aims.This work aims at proving the ability to use slitless spectroscopy for standard-star spectrophotometry and its use to monitor on-site atmospheric transmission as needed, for example, by theVera C. RubinObservatory Legacy Survey of Space and Time supernova cosmology program. We fully deal with the case of a disperser in the filter wheel, which is the configuration chosen in theRubinAuxiliary Telescope. Methods.The theoretical basis of slitless spectrophotometry is at the heart of our forward-model approach to extract spectroscopic information from slitless data. We developed a publicly available software calledSpectractor, which implements each ingredient of the model and finally performs a fit of a spectrogram model directly on image data to obtain the spectrum. Results.We show through simulations that our model allows us to understand the structure of spectrophotometric exposures. We also demonstrate its use on real data by solving specific issues and illustrating that our procedure allows the improvement of the model describing the data. Finally, we discuss how this approach can be used to directly extract atmospheric transmission parameters from the data and thus provide the base for on-site atmosphere monitoring. We show the efficiency of the procedure in simulations and test it on the limited available data set.

Astronomy & Astrophysics↗
DOE OSTI2023

Status of CHIP-TRAP: The Central Michigan University High-Precision Penning Trap

Precise and accurate atomic mass data provide crucial information for applications in a wide range of fields in physics and beyond, including astrophysics, nuclear structure, particle and neutrino physics, fundamental symmetries, chemistry, and metrology. The most precise atomic mass measurements are performed on charged particles confined in a Penning trap. Here, we describe the development, status, and outlook of CHIP-TRAP: the Central Michigan University high-precision Penning trap. CHIP-TRAP aims to perform ultra-high precision (~1 part in 10 11 fractional precision) mass measurements on stable and long-lived isotopes produced with external ion sources and transported to the Penning traps. Along the way, ions of a particular m/q are selected with a multi-reflection time-of-flight mass separator (MR-TOF-MS), with further filtering performed in a cylindrical capture trap before the ions are transported to a pair of hyperbolic measurement traps. In this paper, we report on the design and status of CHIP-TRAP and present results from the commissioning of the ion sources, MR-TOF-MS, and capture trap. We also provide an outlook on the continued development and commissioning of CHIP-TRAP.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2009

Progressive Classification Using Support Vector Machines

An algorithm for progressive classification of data, analogous to progressive rendering of images, makes it possible to compromise between speed and accuracy. This algorithm uses support vector machines (SVMs) to classify data. An SVM is a machine learning algorithm that builds a mathematical model of the desired classification concept by identifying the critical data points, called support vectors. Coarse approximations to the concept require only a few support vectors, while precise, highly accurate models require far more support vectors. Once the model has been constructed, the SVM can be applied to new observations. The cost of classifying a new observation is proportional to the number of support vectors in the model. When computational resources are limited, an SVM of the appropriate complexity can be produced. However, if the constraints are not known when the model is constructed, or if they can change over time, a method for adaptively responding to the current resource constraints is required. This capability is particularly relevant for spacecraft (or any other real-time systems) that perform onboard data analysis. The new algorithm enables the fast, interactive application of an SVM classifier to a new set of data. The classification process achieved by this algorithm is characterized as progressive because a coarse approximation to the true classification is generated rapidly and thereafter iteratively refined. The algorithm uses two SVMs: (1) a fast, approximate one and (2) slow, highly accurate one. New data are initially classified by the fast SVM, producing a baseline approximate classification. For each classified data point, the algorithm calculates a confidence index that indicates the likelihood that it was classified correctly in the first pass. Next, the data points are sorted by their confidence indices and progressively reclassified by the slower, more accurate SVM, starting with the items most likely to be incorrectly classified. The user can halt this reclassification process at any point, thereby obtaining the best possible result for a given amount of computation time. Alternatively, the results can be displayed as they are generated, providing the user with real-time feedback about the current accuracy of classification.

Wagstaff, Kiri↗
NASA NTRS2019

Implementing Polar Projections with OGC Services for the Enhancement of AIRS NRT Visualization in LANCE

The Atmospheric Infrared Sounder (AIRS) NRT product is one important element in the Land, Atmosphere Near real-time Capability for EOS (LANCE). The LANCE processing of AIRS NRT products and the image generation are performed at the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). The Open Geospatial Consortium (OGC) services are being utilized to access AIRS NRT images. The ongoing AIRS NRT imagery enhancement work includes adding a new set of the images in polar projections. Polar projections are commonly used for mapping Antarctica and Arctic regions. We have implemented more precise south polar (EPSG:3031) projection and north polar (EPSG:3413) projection making our OGC service instances more useful and interoperable. Thus, AIRS NRT data can be easily accessed and integrated with other applications. It greatly increases the impact of our data on researches in polar regions.In this presentation, we will introduce the optimized processing workflow for OGC services from data access with spatial-temporal index to data visualization with different SLD, and demonstrate how to use open source software to provide more precise map images in polar projections.

Zhao, Peisheng↗
DOE OSTI2024

Deep eutectic solvents as green and sustainable diluents in headspace gas chromatography for the determination of trace level genotoxic impurities in pharmaceuticals

Genotoxic impurities (GTIs) are potential carcinogens that need to be controlled down to ppm or lower concentration levels in pharmaceuticals under strict regulations. The static headspace gas chromatography (HS-GC) coupled with electron capture detection (ECD) is an effective approach to monitor halogenated and nitroaromatic genotoxins. Deep eutectic solvents (DESs) possess tunable physico-chemical properties and low vapor pressure for HS-GC methods. In this study, zwitterionic and non-ionic DESs have been used for the first time to develop and validate a sensitive analytical method for the analysis of 24 genotoxins at sub-ppm concentrations. Compared to non-ionic diluents, zwitterionic DESs produced exceptional analytical performance and the betaine: 7 (1,4- butane diol) DES outperformed the betaine: 5 (1,4-butane diol) DES. Limits of detection (LOD) down to the 5-ppb concentration level were achieved in DESs. Wide linear ranges spanning over 5 orders of magnitude (0.005–100 µg g –1 ) were obtained for most analytes with exceptional sensitivities and high precision. The method accuracy and precision were validated using 3 commercially available drug substances and excellent recoveries were obtained. Finally, this study broadens the applicability of HS-GC in the determination of less volatile GTIs by establishing DESs as viable diluent substitutes for organic solvents in routine pharmaceutical analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

ML-driven Strong Lens Discoveries: Down to θ E ~ $0^{_{''}}_{^.}03$ and M halo < 10 11 M ⊙

We present results on extending the strong lens discovery space down to much smaller Einstein radii ( θ E ≲ $0^{_{''}}_{^.}03$) and much lower halo mass (M halo < 10 11 M ⊙ ) through the combination of JWST observations and machine learning (ML) techniques. First, we forecast detectable strong lenses with JWST using CosmoDC2 as the lens catalog, and a source catalog down to 29th magnitude. By further incorporating the VELA hydrodynamical simulations of high-redshift galaxies, we simulate strong lenses. We train a ResNet on these images, achieving near-100% completeness and purity for “conventional” strong lenses ( θ E ≳ $0^{_{''}}_{^.}05$), applicable to JWST, the Hubble Space Telescope (HST), the Roman Space Telescope, and Euclid VIS. For the first time, we also search for very low halo mass strong lenses (M halo < 10 11 M ⊙ ) in simulations, with θ E << $0^{_{''}}_{^.}05$, down to the best resolution ($0^{_{''}}_{^.}03$) and depth (10,000 s) limits of JWST using ResNet. A U-Net model is employed to pinpoint these small lenses in images, which are otherwise virtually impossible for human detection. Our results indicate that JWST can find ∼17/deg 2 such low-halo-mass lenses, with the locations of ∼1.1/deg 2 of these detectable by the U-Net at ∼100% precision (and ∼7.0/deg 2 at a 99.0% precision). To validate our model for finding “conventional” strong lenses, we apply it to HST images, discovering two new strong lens candidates previously missed by human classifiers in a crowdsourcing project (E. O. Garvin et al. 2022). This study demonstrates the (potentially “superhuman”) advantages of ML combined with current and future space telescopes for detecting conventional, and especially, low-halo-mass strong lenses, which are critical for testing cold dark matter models.

Silver, Ethan [Harvard University, Cambridge, MA (↗
NASA NTRS1991

A novel design for a hybrid space manipulator

Described are the structural design, kinematics, and characteristics of a robot manipulator for space applications and use as an articulate and powerful space shuttle manipulator. Hybrid manipulators are parallel-serial connection robots that give rise to a multitude of highly precise robot manipulators. These manipulators are modular and can be extended by additional modules over large distances. Every module has a hemispherical work space and collective modules give rise to highly dexterous symmetrical work space. Some basic designs and kinematic structures of these robot manipulators are discussed, the associated direct and inverse kinematics formulations are presented, and solutions to the inverse kinematic problem are obtained explicitly and elaborated upon. These robot manipulators are shown to have a strength-to-weight ratio that is many times larger than the value that is currently available with industrial or research manipulators. This is due to the fact that these hybrid manipulators are stress-compensated and have an ultralight weight, yet, they are extremely stiff due to the fact that force distribution in their structure is mostly axial. Actuation is prismatic and can be provided by ball screws for maximum precision.

Shahinpoor, MO↗