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At least 595 records · Page 33

All sources NASA NTRS DOE OSTI

NASA NTRS2005

Momentum-Based Dynamics for Spacecraft with Chained Revolute Appendages

An efficient formulation is presented for a sub-class of multi-body dynamics problems that involve a six degree-of-freedom base body and a chain of N rigid linkages connected in series by single degree-of-freedom revolute joints. This general method is particularly well suited for simulations of spacecraft dynamics and control that include the modeling of an orbiting platform with or without internal degrees of freedom such as reaction wheels, dampers, and/or booms. In the present work, particular emphasis is placed on dynamic simulation of multi-linkage robotic manipulators. The differential equations of motion are explicitly given in terms of linear and angular momentum states, which can be evaluated recursively along a serial chain of linkages for an efficient real-time solution on par with the best of the O(N3) methods.

Queen, Steven↗

NASA NTRS2002

THz frequency multiplier chains base on planar Schottky diodes

The Herschel Space Observatory (HSO), an ESA cornerstone mission with NASA contribution, will enable a comprehensive study of the galactic as well as the extra galactic universe. At the heart of this exploration are ultra sensitive coherent detectors that can allow for high-resolution spectroscopy. Successful operation of these receivers is predicated on providing a sufficiently powerful local oscillator (LO) source. Historically, a versatile space qualified LO source for frequencies beyond 500 GHz has been difficult if not impossible. This paper will focus on the effort under way to develop, build, characterize and qualify a LO chain to 1200 GHz (Band 5 on HSO) that is based on planar GaAs diodes mounted in waveguide circuits. State-of-the-art performance has been obtained from a three-stage ( x2 x 2 x 3 ) multiplier chain that can provide a peak output power of 120 uW (1178 GHz) at room temperature and a peak output power of 190 uW at 1183 GHz when cooled to 113 K. Implementation of this LO source for the Heterodyne Instrument for Far Infrared (HIFI) on HSO will be discussed in detail.

oscillator spectroscopy↗

NASA NTRS1988

Cross-contact chain

A system is provided for use with wafers that include multiple integrated circuits that include two conductive layers in contact at multiple interfaces. Contact chains are formed beside the integrated circuits, each contact chain formed of the same two layers as the circuits, in the form of conductive segments alternating between the upper and lower layers and with the ends of the segments connected in series through interfaces. A current source passes a current through the series-connected segments, by way of a pair of current tabs connected to opposite ends of the series of segments. While the current flows, voltage measurements are taken between each of a plurality of pairs of voltage tabs, the two tabs of each pair connected to opposite ends of an interface that lies along the series-connected segments. A plot of interface conductances on a normal probability chart, enables prediction of the yield of good integrated circuits from the wafer.

Lieneweg, Udo↗

NASA NTRS2010

Harnessing the Risk-Related Data Supply Chain: An Information Architecture Approach to Enriching Human System Research and Operations Knowledge

NASA's Human Research Program (HRP) and Space Life Sciences Directorate (SLSD), not unlike many NASA organizations today, struggle with the inherent inefficiencies caused by dependencies on heterogeneous data systems and silos of data and information spread across decentralized discipline domains. The capture of operational and research-based data/information (both in-flight and ground-based) in disparate IT systems impedes the extent to which that data/information can be efficiently and securely shared, analyzed, and enriched into knowledge that directly and more rapidly supports HRP's research-focused human system risk mitigation efforts and SLSD s operationally oriented risk management efforts. As a result, an integrated effort is underway to more fully understand and document how specific sets of risk-related data/information are generated and used and in what IT systems that data/information currently resides. By mapping the risk-related data flow from raw data to useable information and knowledge (think of it as the data supply chain), HRP and SLSD are building an information architecture plan to leverage their existing, shared IT infrastructure. In addition, it is important to create a centralized structured tool to represent risks including attributes such as likelihood, consequence, contributing factors, and the evidence supporting the information in all these fields. Representing the risks in this way enables reasoning about the risks, e.g. revisiting a risk assessment when a mitigation strategy is unavailable, updating a risk assessment when new information becomes available, etc. Such a system also provides a concise way to communicate the risks both within the organization as well as with collaborators. Understanding and, hence, harnessing the human system risk-related data supply chain enhances both organizations' abilities to securely collect, integrate, and share data assets that improve human system research and operations.

Buquo, Lynn↗

NASA NTRS2011

Harnessing the Risk-Related Data Supply Chain: An Information Architecture Approach to Enriching Human System Research and Operations Knowledge

An Information Architecture facilitates the understanding and, hence, harnessing of the human system risk-related data supply chain which enhances the ability to securely collect, integrate, and share data assets that improve human system research and operations. By mapping the risk-related data flow from raw data to useable information and knowledge (think of it as a data supply chain), the Human Research Program (HRP) and Space Life Science Directorate (SLSD) are building an information architecture plan to leverage their existing, and often shared, IT infrastructure.

Buquo, Lynn E.↗

NASA NTRS2011

Consequence and Resilience Modeling for Chemical Supply Chains

The U.S. chemical sector produces more than 70,000 chemicals that are essential material inputs to critical infrastructure systems, such as the energy, public health, and food and agriculture sectors. Disruptions to the chemical sector can potentially cascade to other dependent sectors, resulting in serious national consequences. To address this concern, the U.S. Department of Homeland Security (DHS) tasked Sandia National Laboratories to develop a predictive consequence modeling and simulation capability for global chemical supply chains. This paper describes that capability , which includes a dynamic supply chain simulation platform called N_ABLE(tm). The paper also presents results from a case study that simulates the consequences of a Gulf Coast hurricane on selected segments of the U.S. chemical sector. The case study identified consequences that include impacted chemical facilities, cascading impacts to other parts of the chemical sector. and estimates of the lengths of chemical shortages and recovery . Overall. these simulation results can DHS prepare for and respond to actual disruptions.

Stamber, Kevin L.↗

NASA NTRS2012

Observations of Carbon Chain Chemistry in the Envelopes of Low-Mass Protostars

Observational results are reported from our surveys in the Northern Hemisphere (using the Onsala 20 m telescope) and the Southern Hemisphere (using the Mopra 22 m telescope) to search for 3 mm emission lines from carbon-chain-bearing species and other complex molecules in the envelopes of low-mass protostars. Based on a sample of approximately 60 sources, we find that carbon-chain-bearing species including HC3N (and C4H) are highly abundant in the vicinity of more than half of the observed protostars. The origin and evolution of these species, including their likely incorporation into ices in protoplanetary disks will be discussed

Cordiner, M.↗

NASA NTRS2012

Microchip Non-Aqueous Capillary Electrophoresis (MicronNACE) Method to Analyze Long-Chain Primary Amines

A protocol was developed as a first step in analyzing the complex organic aerosols present on Saturn's moon Titan, as well as the analogues of these aerosols (tholins) made on Earth. Labeling of primary amines using Pacific Blue succinimidyl ester is effected in ethanol with 25 mM triethylamine to maintain basic conditions. This reaction is allowed to equilibrate for at least one hour. Separation of the labeled primary amines is performed in ethanol with 1.05 M acetic acid, and 50 mM ammonium acetate in a commercial two-layer glass device with a standard crossmicrochannel measuring 50 microns wide by 20 microns deep. Injection potentials are optimized at 2 kV from the sample (negative) to the waste well (positive), with slight bias applied to the other two wells ( 0.4 and 0.8 V) to pinch the injection plug for the 30-s injection. Separation is performed at a potential of 5 kV along the channel, which has an effective separation distance of 7 cm. The use of ethanol in this method means that long-chain primary amines can be dissolved. Due to the low pH of the separation buffer, electro-osmotic flow (EOF) is minimized to allow for separation of both short-chain and longchain amines. As the freezing point of ethanol is much lower than water, this protocol can perform separations at temperatures lower than 0 C, which would not be possible in aqueous phase. This is of particular importance when considering in situ sampling of Titan aerosols, where unnecessary heating of the sample (even to room temperature) would lead to decomposition or unpredictable side reactions, which would make it difficult to characterize the sample appropriately.

Willis, Peter A.↗

NASA NTRS2013

Application and Evaluation of a Snowmelt Runoff Model in the Tamor River Basin, Eastern Himalaya Using a Markov Chain Monte Carlo (MCMC) Data Assimilation Approach

Previous studies have drawn attention to substantial hydrological changes taking place in mountainous watersheds where hydrology is dominated by cryospheric processes. Modelling is an important tool for understanding these changes but is particularly challenging in mountainous terrain owing to scarcity of ground observations and uncertainty of model parameters across space and time. This study utilizes a Markov Chain Monte Carlo data assimilation approach to examine and evaluate the performance of a conceptual, degree-day snowmelt runoff model applied in the Tamor River basin in the eastern Nepalese Himalaya. The snowmelt runoff model is calibrated using daily streamflow from 2002 to 2006 with fairly high accuracy (average Nash-Sutcliffe metric approx. 0.84, annual volume bias <3%). The Markov Chain Monte Carlo approach constrains the parameters to which the model is most sensitive (e.g. lapse rate and recession coefficient) and maximizes model fit and performance. Model simulated streamflow using an interpolated precipitation data set decreases the fractional contribution from rainfall compared with simulations using observed station precipitation. The average snowmelt contribution to total runoff in the Tamor River basin for the 2002-2006 period is estimated to be 29.7+/-2.9% (which includes 4.2+/-0.9% from snowfall that promptly melts), whereas 70.3+/-2.6% is attributed to contributions from rainfall. On average, the elevation zone in the 4000-5500m range contributes the most to basin runoff, averaging 56.9+/-3.6% of all snowmelt input and 28.9+/-1.1% of all rainfall input to runoff. Model simulated streamflow using an interpolated precipitation data set decreases the fractional contribution from rainfall versus snowmelt compared with simulations using observed station precipitation. Model experiments indicate that the hydrograph itself does not constrain estimates of snowmelt versus rainfall contributions to total outflow but that this derives from the degree-day melting model. Lastly, we demonstrate that the data assimilation approach is useful for quantifying and reducing uncertainty related to model parameters and thus provides uncertainty bounds on snowmelt and rainfall contributions in such mountainous watersheds.

runoff↗

NASA NTRS2015

Thermal Analysis of Brazing Seal and Sterilizing Technique to Break Contamination Chain for Mars Sample Return

The potential to return Martian samples to Earth for extensive analysis is in great interest of the planetary science community. It is important to make sure the mission would securely contain any microbes that may possibly exist on Mars so that they would not be able to cause any adverse effects on Earth's environment. A brazing sealing and sterilizing technique has been proposed to break the Mars-to-Earth contamination chain. Thermal analysis of the brazing process was conducted for several conceptual designs that apply the technique. Control of the increase of the temperature of the Martian samples is a challenge. The temperature profiles of the Martian samples being sealed in the container were predicted by finite element thermal models. The results show that the sealing and sterilization process can be controlled such that the samples' temperature is maintained below the potentially required level, and that the brazing technique is a feasible approach to break the contamination chain.

Bao, Xiaoqi↗

NASA NTRS2018

Compact 1.9 THz Multi-Pixel Local Oscillator Chain

Single-pixel heterodyne receivers are severely limited in their capability to map large areas on the sky. We report on the development of THz multi-pixel local oscillator sources that ought to enable THz array receivers of the future. We demonstrate a prototype 16-pixel chain at 1.9 THz. Output power in excess of >10 microwatts has been demonstrated per pixel from this compact chain.

Lin, Robert↗

NASA NTRSDate not supplied

The Application of Remote Sensing and Machine Learning to Improve Early Warning Systems for Harmful Algal Events in the Highland Lake Chain, TX

Beginning in 2019, harmful algal events have caused canine deaths in both Lady Bird Lake and Lake Travis located near Austin, Texas. These two reservoirs are part of the larger Highland Lakes chain, managed by the City of Austin Department of Watershed Protection (COA DWP) and the Lower Colorado River Authority (LCRA), which fulfill municipal, commercial, and agricultural water demands. Given the recent increase in favorable environmental conditions for algal events in central Texas, NASA DEVELOP partnered with LCRA and COA DWP to improve monitoring and early detection of algal events, utilizing satellite remote sensing and machine learning. Spatially and temporally varied chlorophyll a concentrations, cyanobacteria detections, turbidity, and water surface temperature products are used as environmental proxies. Landsat 8 Operational Land Imager (OLI) and the Sentinel-2 MultiSpectral Instrument (MSI) data were used to provide a combined revisit time of up to ~3 days and < 30 m per pixel products. Chlorophyll a concentrations were estimated using a pre-trained Mixture Density Network, and cyanobacteria detection was accomplished using the Broad Wavelength Algae Index, which can differentiate algal blooms from algal proliferations (mats). In situ data were used to validate remotely sensed measurements and quantify uncertainties. Preliminary results show a good fit between the modeled output and in situ observations, suggesting that remote sensing data can be used to retrieve biogeochemical properties and/or inherent optical properties (IOPs) of water columns in these inland human-made lakes. Uncertainties were introduced from the sensitivity to atmospheric correction, inherent mismatch between satellite and sampling data, and a relatively lower signal-to-noise ratio over water. The resulting products enable near real-time monitoring of environmental proxies relevant to algal event presence in the Highland Lakes chain, and will ultimately support water management, decision making, and risk communication.

Shuyu Chang↗

NASA NTRS2021

The Chain-link Actuator: Exploiting the Bending Stiffness of McKibben Artificial Muscles to Achieve Larger Contraction Ratios

McKibben artificial muscles, comprised of an ex-pandable bladder wrapped in a double-helix-braided sheath,have the ability to generate forces without restricting motion tooccur exclusively along the direction of actuation. This makesthem attractive for a variety of applications including soft,wearable, and biomimetic robots. Despite their advantages, thetheoretical maximum contraction ratio of McKibben muscles isonly 36.3%, which restricts the range of motion of the systemsthey actuate. This work introduces a novel ‘chain-link actuator’that exploits the bending stiffness of McKibben muscles toachieve contraction ratios of more than 50%. A static modelthat captures the relationship between pressure, displacement,and force is presented and validated on several real chain-linkactuator systems.

Daniel Bruder↗

NASA NTRSDate not supplied

Additive Manufacturing: Disrupting Global Supply Chains and Enabling Sustainable Development

The integration of new materials and innovative manufacturing technologies into product supply chains are critically needed to address human and societal needs and to promote sustainable development and economic competitiveness. Recently, there has been tremendous growth in the additive manufacturing (AM) landscape with the introduction of high- end machines suitable for industrial applications. In addition, availability of desktop 3-D printers as well as open source printers and platforms have also facilitated the large scale growth of distributed manufacturing. The paradigm shift in thinking, where one can turn their design into product on demand, is leading to new business models and challenging traditional models of product development and distribution. In this presentation, an overview of different AM technologies will be provided along with technical challenges and opportunities. Various examples of materials (polymers, ceramics, metals, hybrids, and multi material systems) and structures achieved from utilizing a wide variety of additive manufacturing approaches will be provided. Technical challenges and opportunities for the utilization of additive manufacturing as a powerful enabler for sustainable development and disruptive technological threat to global supply chains for different materials and systems will be presented.

Additive Manufacturing↗

NASA NTRS2024

High-Order/Low-Dissipation Chain-Rule Flux Solution Reconstruction Schemes in FUN3D

In this paper, we report progress in the development of economically high-order flux-solution-reconstruction (FSR) schemes, which are second-order accurate on general unstructured grids but achieve high-order accuracy when a grid is regular, i.e., has the same stencil (with the same spacing) throughout the domain. Two variants of the FSR schemes are discussed: chain-rule-flux-solution reconstruction (CFSR) and quadratic-form-flux-solution reconstruction (QFSR), where the former is based on the chain rule and the latter on the flux reconstruction expressed as a function of solution variables. These schemes are tested for flows with shock waves with a limiter incorporated in the flux and solution reconstructions. Improved results, compared with second-order methods are demonstrated for inviscid and viscous flows with smooth grids.

high-order↗

NASA NTRS2020

Shape Estimation for Elongated Deformable Object using B-spline Chained Multiple Random Matrices Model

In this paper, a B-spline chained multiple random matrix models (RMMs) representation is proposed to model geometric characteristics of an elongated deformable object. The hyper degrees of freedom structure of the elongated deformable object make its shape estimation challenging. Based on the likelihood function of the proposed B-spline chained multiple RMMs, an expectation-maximization (EM) method is derived to estimate the shape of the elongated deformable object. A split and merge method based on the Euclidean minimum spanning tree (EMST) is proposed to provide initialization for the EM algorithm. The proposed algorithm is evaluated for the shape estimation of the elongated deformable objects in scenarios, such as the static rope with various configurations (including configurations with intersection), the continuous manipulation of a rope and a plastic tube, and the assembly of two plastic tubes. The execution time is computed and the accuracy of the shape estimation results is evaluated based on the comparisons between the estimated width values and its ground-truth, and the intersection over union (IoU) metric.

Gang Yao↗

DOE OSTI2020

Approximate Inverse Chain Preconditioner: Iteration Count Case Study for Spectral Support Solvers

As the growing availability of computational power slows, there has been an increasing reliance on algorithmic advances. However, faster algorithms alone will not necessarily bridge the gap in allowing computational scientists to study problems at the edge of scientific discovery in the next several decades. Often, it is necessary to simplify or precondition solvers to accelerate the study of large systems of linear equations commonly seen in a number of scientific fields. Preconditioning a problem to increase efficiency is often seen as the best approach; yet, preconditioners which are fast, smart, and efficient do not always exist. Following the progress of [1], we present a new preconditioner for symmetric diagonally dominant (SDD) systems of linear equations. These systems are common in certain PDEs, network science, and supervised learning among others. Based on spectral support graph theory, this new preconditioner builds off of the work of [2], computing and applying a V-cycle chain of approximate inverse matrices. This preconditioner approach is both algebraic in nature as well as hierarchically-constrained depending on the condition number of the system to be solved. Due to its generation of an Approximate Inverse Chain of matrices, we refer to this as the AIC preconditioner. We further accelerate the AIC preconditioner by utilizing precomputations to simplify setup and multiplications in the con-text of an iterative Krylov-subspace solver. While these iterative solvers can greatly reduce solution time, the number of iterations can grow large quickly in the absence of good preconditioners. Initial results for the AIC preconditioner have shown a very large reduction in iteration counts for SDD systems as compared to standard preconditioners such as Incomplete Cholesky (ICC) and Multigrid (MG). We further show significant reduction in iteration counts against the more advanced Combinatorial Multigrid (CMG) preconditioner. We have further developed no-fill sparsification techniques to ensure that the computational cost of applying the AIC preconditioner does not grow prohibitively large as the depth of the V-cycle grows for systems with larger condition numbers. Our numerical results have shown that these sparsifiers maintain the sparsity structure of our system while also displaying significant reductions in iteration counts.1 2

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Approximate Inverse Chain Preconditioner: Iteration Count Case Study for Spectral Support Solvers

97 MATHEMATICS AND COMPUTING↗