CCSDS Implementation, Concept, and Architecture of the Psyche Mission's End-to-End Information System (EEIS)
No abstract provided
Sirohi, Richa↗
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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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Planetary In Situ Capillary Electrophoresis System for End-to-End Analysis on Life Detection Missions
No abstract provided
Willis, Peter↗
End-to-End System Considerations for Space Communications System
No abstract provided
Cheung, Kar-Ming↗
Actuator and Motor Control End-to-End V&V on the Mars 2020 Rover
The Mars 2020 Perseverance rover is the most advanced robotic exploration system ever sent to another planet. To support the complex scientific and mobility needs of the mission, the rover utilizes 33 actuators, three multi-degree-of-freedom force-torque sensors, fifteen single or dual-speed resolvers, two solenoid valves, and twelve contact switches. The control for these actuators and sensors is achieved by several levels of flight software, coordinated between two computers with varying bandwidth control loops. Furthermore, the actuators and sensors were integrated into multiple larger robotic mechanisms that were delivered by different organizations at various points in the Integration and Test (I&T) timeline. All of this created a very complex Verification and Validation (V&V) scenario involving multiple subsystems and teams, several hardware and software testbeds with varying levels of fidelity, and significant systems engineering to ensure the overall I&T schedule could be maintained while ensuring system hardware safety.This paper details the integrated V&V effort across multiple teams and venues to provide full coverage of all necessary functionality, performance, and fault protection. First, it provides an overview of how the V&V campaign was subdivided among teams and venues and provides descriptions of the various hardware configurations used to support the testing. The Mars 2020 implementation of the plan incorporates many of the lessons learned from Mars Science Laboratory’s test campaign, and these value-added modifications are discussed here. Also included in this section is the system-level environmental testing approach used for mechanisms. Second, the paper describes the phased approach used by the teams to support new hardware and software deliveries to testbed and Systems I&T. In this approach the test campaign was built upon higher-level mechanism needs for performance, functionality, and safety at specific times in the campaign. Finally, the paper discusses lessons learned from the V&V campaign that should be applied to future large-scale motion control testing efforts.
Borne, Davis↗
LOFTID Aeroshell Thermal Response Uncertainty Analysis Utilizing the End-to-End Monte Carlo Approach
A probabilistic thermal margin process has been performed to design the flexible thermal protection system (FTPS) and select entry trajectory constraints given an acceptable risk level for the Low-Earth Orbit Flight Test of and Inflatable Decelerator (LOFTID) project. Uncertainties exist in atmospheric entry aeroheating environments and the predicted thermal response of thermal protection system (TPS) material. Entry vehicle TPS is often over-sized to mitigate uncertainty by combining conservative bounding scenarios together. The probabilistic thermal margin process allows engineers to make informed aeroshell design, flight design, and FTPS performance risk trades while preventing excessive FTPS margin from being applied. This paper describes the uncertainty analysis methodology used to carry out a probabilistic thermal margin process used for LOFTID’s aeroshell and explains how the calculated probability of exceeding flight allowable temperatures is used to design the FTPS and establish nominal flight design constraints. This probabilistic thermal margin process had never been applied to entry, decent, and landing design for a flown entry vehicle and it is one of the LOFTID project’s goals to demonstrate its merits.
Steven Andrew Tobin↗
End-To-End Uncertainty Quantification with Analytical Derivatives for Design Under Uncertainty
Uncertainty quantification (UQ) is a rapidly growing and evolving discipline, especially within the aerospace community. Performing analysis with UQ can provide decision makers with a wealth of information about a candidate design. However, the value of UQ is fully realized when the information gained during UQ analysis is leveraged in a feedback loop of a design optimization process, often referred to as design under uncertainty. Although design under uncertainty can be a powerful risk mitigation technique, there are a number of roadblocks that prevent its implementation. Two primary factors are computational costs and added complexity of the analysis. High fidelity simulations on the order tens of uncertain variables quickly become computationally infeasible. Also, implementing UQ into an existing multidisciplinary design and optimization (MDO) process often requires extensive knowledge of the UQ methods and careful treatment of the problem formulation. The objective of this work is to address these two primary roadblocks and enable practitioners to efficiently perform design under uncertainty with limited knowledge of the UQ discipline. Methods outlined in this paper demonstrate MDO incorporating UQ into the design process, leveraging an analytic derivative tool chain through the entire optimization. The proposed approach leverages machine learning techniques to generate a differentiable confidence interval output from polynomial chaos models. This technique, coupled with the incorporation of analytical derivatives through the Polynomial Chaos Expansion (PCE) process, eliminates the need to estimate derivatives which are usually obtained from finite difference, complex step, or similar methods. Developing a differentiable confidence interval allows mixed uncertainty problems (both epistemic and aleatory) to be modeled. Without such modeling, these problems cannot accurately predict objective functions containing statistical quantities such as mean and variance. The addition of analytic derivatives to a polynomial chaos-based UQ method decreases the computational costs of performing design under uncertainty by orders of magnitude in comparison with methods such as complex step. The method and codes developed are modular in nature and are a drop-in solution for design under uncertainty within existing MDO problems. A low-fidelity analytical multidisciplinary optimization under uncertainty for a wing design in OpenMDAO is detailed in this paper. This demonstration case will include both objective functions and constraints which are influenced by uncertain parameters.
Ben D Phillips↗
End-To-End Uncertainty Quantification with Analytical Derivatives for Design Under Uncertainty
Uncertainty quantification (UQ) is a rapidly growing and evolving discipline, especially within the aerospace community. Performing analysis with UQ can provide decision makers with a wealth of information about a candidate design. However, the value of UQ is fully realized when the information gained during UQ analysis is leveraged in a feedback loop of a design optimization process, often referred to as design under uncertainty. Although design under uncertainty can be a powerful risk mitigation technique, there are a number of roadblocks that prevent its implementation. Two primary factors are computational costs and added complexity of the analysis. High fidelity simulations on the order tens of uncertain variables quickly become computationally infeasible. Also, implementing UQ into an existing multidisciplinary design and optimization (MDO) process often requires extensive knowledge of the UQ methods and careful treatment of the problem formulation. The objective of this work is to address these two primary roadblocks and enable practitioners to efficiently perform design under uncertainty with limited knowledge of the UQ discipline. Methods outlined in this paper demonstrate MDO incorporating UQ into the design process, leveraging an analytic derivative tool chain through the entire optimization. The proposed approach leverages machine learning techniques to generate a differentiable confidence interval output from polynomial chaos models. This technique, coupled with the incorporation of analytical derivatives through the Polynomial Chaos Expansion (PCE) process, eliminates the need to estimate derivatives which are usually obtained from finite difference, complex step, or similar methods. Developing a differentiable confidence interval allows mixed uncertainty problems (both epistemic and aleatory) to be modeled. Without such modeling, these problems cannot accurately predict objective functions containing statistical quantities such as mean and variance. The addition of analytic derivatives to a polynomial chaos-based UQ method decreases the computational costs of performing design under uncertainty by orders of magnitude in comparison with methods such as complex step. The method and codes developed are modular in nature and are a drop-in solution for design under uncertainty within existing MDO problems. A low-fidelity analytical multidisciplinary optimization under uncertainty for a wing design in OpenMDAO is detailed in this paper. This demonstration case will include both objective functions and constraints which are influenced by uncertain parameters.
Ben Phillips↗
MAAP: A Cloud-Native Platform for End-to-End EO Open Science
Explore the source record for details and available documents.
Rajat Shinde↗
End-to-End Uncertainty Quantification with Analytical Derivatives for Design Under Uncertainty
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Ben D. Phillips↗
Transformer End-to-End Optimization of Compressive LiDARs Using Imaging Spectroscopy Side Information
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Nestor Porras-Diaz↗
Benchmarking and end-to-end considerations for GeoAI-enabled decision making
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Yang, Lexie↗
End-to-End Encryption for Cyber-Physical Systems Using Fully Homomorphic Encryption
Cyber-physical systems require reliable, safe, and secure control of critical infrastructure, combining computational and networking capabilities, which heighten the risk of cyber attacks. These attacks can disrupt the physical process, causing unforeseen consequences. One solution is the use of fully homomorphic encryption (FHE) to protect the control loop, allowing for secure computations and communications without compromising signal and control system privacy. The challenge with FHE, however, is its requirement for inputs to be integers. This presentation introduces a modified Learning With Errors (LWE) FHE approach that encodes control system dynamics and signals into integers. Our proposed scheme leverages a generalized LWE encoding function and modifies the Gentry-Sahai-Waters gadget decomposition tool to encrypt the control system. Using the modified LWE scheme, we formalize a fully encrypted control system, supported by simulated results.
97 MATHEMATICS AND COMPUTING↗
Demystifying the Resilience of Large Language Models: An End-to-End Perspective
Deep neural networks are known to be resilient to random bit-wise faults in their parameters. However, this resilience has primarily been established through evaluations of classification models. The extent to which this claim holds for large-language models remains underexplored. In this work, we conduct an extensive measurement study on the impact of random bitwise faults in commercial-scale language models. We perform an in-depth analysis of the resulting generation outputs. We first expose that these language models are not truly resilient to random bit-flips. While aggregate metrics such as accuracy may suggest resilience, an in-depth inspection of the generated outputs shows significant degradation in text quality. Our analysis also shows that tasks requiring more complex reasoning suffer more from performance and quality degradation. Moreover, we extend our analysis to models with augmented reasoning capabilities, such as Chain-of-Thought or Mixture of Experts architectures, and characterize their failure scenarios under random bit-flips.
Sun, Yu↗
BRE‐X Emissions Database for End‐of‐Life Scenarios of Selective Building Construction Materials to Enable Circular Economy in Construction
In the United States, construction and demolition debris predominately end up in landfills with minimal end‐of‐life Re‐X (recover, recycle, reuse, etc.) scenarios, resulting in large environmental impacts and lost opportunities for material recovery. Except for concrete and metals, which seem to have a few well‐defined end‐of‐life pathways, there seems to be a lack of well‐documented end‐of‐life scenarios for other construction materials, let alone their emissions data. Hence, there is a need for documented end‐of‐life Re‐X scenarios and end‐of‐life data of more building materials to motivate widespread use of Re‐X strategies in building design. This paper outlines the efforts of the National Renewable Energy Laboratory, Carbon Leadership Forum, Building Transparency, and Skidmore, Owings & Merrill to (a) create an open‐access BRE‐X (Building Re‐X) end‐of‐life emissions database consisting of greenhouse gas emissions data associated with various end‐of‐life scenarios for a select list of high‐impact building construction materials, and (b) integrate the BRE‐X end‐of‐life emissions database with CAD/BIM/LCA tools for evaluating various end‐of‐life scenarios. The paper also presents a few existing life cycle inventory databases that contain sparse amounts of end‐of‐life data for a few construction materials and their limitations in terms of scaling and data consolidation. Finally, a sample of how the collected data can be ingested into whole‐building LCA tools using open data formats and a public access link to the BRE‐X end‐of‐life emissions database is also included.
36 MATERIALS SCIENCE↗
Robotic End Effectors for Hard-Rock Climbing
Special-purpose robot hands (end effectors) now under development are intended to enable robots to traverse cliffs much as human climbers do. Potential applications for robots having this capability include scientific exploration (both on Earth and other rocky bodies in space), military reconnaissance, and outdoor search and rescue operations. Until now, enabling robots to traverse cliffs has been considered too difficult a task because of the perceived need of prohibitively sophisticated planning algorithms as well as end effectors as dexterous as human hands. The present end effectors are being designed to enable robots to attach themselves to typical rock-face features with less planning and simpler end effectors. This advance is based on the emulation of the equipment used by human climbers rather than the emulation of the human hand. Climbing-aid equipment, specifically cams, aid hooks, and cam hooks, are used by sport climbers when a quick ascent of a cliff is desired (see Figure 1). Currently two different end-effector designs have been created. The first, denoted the simple hook emulator, consists of three "fingers" arranged around a central "palm." Each finger emulates the function of a particular type of climbing hook (aid hook, wide cam hook, and a narrow cam hook). These fingers are connected to the palm via a mechanical linkage actuated with a leadscrew/nut. This mechanism allows the fingers to be extended or retracted. The second design, denoted the advanced hook emulator (see Figure 2), shares these features, but it incorporates an aid hook and a cam hook into each finger. The spring-loading of the aid hook allows the passive selection of the type of hook used. The end effectors can be used in several different modes. In the aid-hook mode, the aid hook on one of the fingers locks onto a horizontal ledge while the other two fingers act to stabilize the end effector against the cliff face. In the cam-hook mode, the broad, flat tip of the cam hook is inserted into a non-horizontal crack in the cliff face. A subsequent transfer of weight onto the end effector causes the tip to rotate within the crack, creating a passive, self-locking action of the hook relative to the crack. In the advanced hook emulator, the aid hook is pushed into its retracted position by contact with the cliff face as the cam hook tip is inserted into the crack. When a cliff face contains relatively large pockets or cracks, another type of passive self-locking can be used. Emulating the function of the piece of climbing equipment called a "cam" (note: not the same as a "cam hook"; see Figure 1), the fingers can be fully retracted and the entire end effector inserted into the feature. The fingers are then extended as far as the feature allows. Any weight then transferred to the end effector will tend to extend the fingers further due to frictional force, passively increasing the grip on the feature. In addition to the climbing modes, these end effectors can be used to walk on (either on the palm or the fingertips) and to grasp objects by fully extending the fingers.
Kennedy, Brett↗
Space-based multifunctional end effector systems functional requirements and proposed designs
The end effector is an essential element of teleoperator and telerobot systems to be employed in space in the next decade. The report defines functional requirements for end effector systems to perform operations that are currently only feasible through Extra-Vehicular Activity (EVA). Specific tasks and functions that the end effectors must be capable of performing are delineated. Required capabilities for forces and torques, clearances, compliance, and sensing are described, using current EVA requirements as guidelines where feasible. The implications of these functional requirements on the elements of potential end effector systems are discussed. The systems issues that must be considered in the design of space-based manipulator systems are identified; including impacts on subsystems tightly coupled to the end effector, i.e., control station, information processing, manipulator arm, tool and equipment stowage. Possible end effector designs are divided into three categories: single degree-of-freedom end effectors, multiple degree of freedom end effectors, and anthropomorphic hands. Specific design alternatives are suggested and analyzed within the individual categories. Two evaluations are performed: the first considers how well the individual end effectors could substitute for EVA; the second compares how manipulator systems composed of the top performers from the first evaluation would improve the space shuttle Remote Manipulator System (RMS) capabilities. The analysis concludes that the anthropomorphic hand is best-suited for EVA tasks. A left- and right-handed anthropomorphic manipulator arm configuration is suggested as appropriate to be affixed to the RMS, but could also be used as part of the Smart Front End for the Orbital Maneuvering Vehicle (OMV). The technical feasibility of the anthropomorphic hand and its control are demonstrated. An evolutionary development approach is proposed and approximate scheduling provided for implementing the suggested manipulator systems in time for space stations operations in the early 1990s.
Mishkin, A. H.↗
Effect of cellulose reducing ends and primary hydroxyl groups modifications on cellulose-cellulase interactions and cellulose hydrolysis
Cellulose reducing ends are believed to play a vital role in the cellulose recalcitrance to enzymatic conversion. However, their role in insoluble cellulose accessibility and hydrolysis is not clear. Thus, in this study, reducing ends of insoluble cellulose derived from various sources were modified by applying reducing and/or oxidizing agents. Here, the effects of cellulose reducing ends modification on cellulose reducing ends, cellulose structure, and cellulose accessibility to cellulase were evaluated along with the impact on cellulose hydrolysis with complete as well purified cellulase components. Sodium borohydride (NaBH 4 ) reduction and sodium chlorite-acetic acid (SC/AA) oxidation were able to modify more than 90% and 60% of the reducing ends, respectively, while the bicinchoninic acid (BCA) reagent applied for various cycles oxidized cellulose reducing ends to various extents. X-ray diffractograms of the treated solids showed that these treatments did not change the cellulose crystalline structure and the change in crystallinity index was insignificant. Surprisingly, it was found that the cellulose reducing ends modification, either through selective NaBH 4 reduction or BCA oxidation, had a negligible impact on cellulose accessibility as well on cellulose hydrolysis rates or final conversions with complete cellulase at loadings as low as 0.5 mg protein/g cellulose. In fact, in contrast to what is traditionally believed, modifications of cellulose reducing ends by these two methods had no apparent impact on cellulose conversion with purified cellulase components and their synergy. However, SC/AA oxidation resulted in significant drop in cellulose conversion (10%–50%) with complete as well purified cellulase components. Nonetheless, further research revealed that the cause for drop in cellulose conversion for the SC/AA oxidation case was due to primary hydroxyl groups (PHGs) oxidation and not the oxidation of reducing ends. Furthermore, it was found that the PHGs modification affects cellulose accessibility and slows the cellulase uptake as well resulting in significant drop in cellulose conversions.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Finding the global minimum: a fuzzy end elimination implementation
The 'fuzzy end elimination theorem' (FEE) is a mathematically proven theorem that identifies rotameric states in proteins which are incompatible with the global minimum energy conformation. While implementing the FEE we noticed two different aspects that directly affected the final results at convergence. First, the identification of a single dead-ending rotameric state can trigger a 'domino effect' that initiates the identification of additional rotameric states which become dead-ending. A recursive check for dead-ending rotameric states is therefore necessary every time a dead-ending rotameric state is identified. It is shown that, if the recursive check is omitted, it is possible to miss the identification of some dead-ending rotameric states causing a premature termination of the elimination process. Second, we examined the effects of removing dead-ending rotameric states from further considerations at different moments of time. Two different methods of rotameric state removal were examined for an order dependence. In one case, each rotamer found to be incompatible with the global minimum energy conformation was removed immediately following its identification. In the other, dead-ending rotamers were marked for deletion but retained during the search, so that they influenced the evaluation of other rotameric states. When the search was completed, all marked rotamers were removed simultaneously. In addition, to expand further the usefulness of the FEE, a novel method is presented that allows for further reduction in the remaining set of conformations at the FEE convergence. In this method, called a tree-based search, each dead-ending pair of rotamers which does not lead to the direct removal of either rotameric state is used to reduce significantly the number of remaining conformations. In the future this method can also be expanded to triplet and quadruplet sets of rotameric states. We tested our implementation of the FEE by exhaustively searching ten protein segments and found that the FEE identified the global minimum every time. For each segment, the global minimum was exhaustively searched in two different environments: (i) the segments were extracted from the protein and exhaustively searched in the absence of the surrounding residues; (ii) the segments were exhaustively searched in the presence of the remaining residues fixed at crystal structure conformations. We also evaluated the performance of the method for accurately predicting side chain conformations. We examined the influence of factors such as type and accuracy of backbone template used, and the restrictions imposed by the choice of potential function, parameterization and rotamer database. Conclusions are drawn on these results and future prospects are given.
NASA Program Exobiology↗