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At least 1,171 records · Page 65

The navigation system of the JPL robot

The control structure of the JPL research robot and the operations of the navigation subsystem are discussed. The robot functions as a network of interacting concurrent processes distributed among several computers and coordinated by a central executive. The results of scene analysis are used to create a segmented terrain model in which surface regions are classified by traversibility. The model is used by a path planning algorithm, PATH, which uses tree search methods to find the optimal path to a goal. In PATH, the search space is defined dynamically as a consequence of node testing. Maze-solving and the use of an associative data base for context dependent node generation are also discussed. Execution of a planned path is accomplished by a feedback guidance process with automatic error recovery.

Thompson, A. M.↗

Admittance model for the shuttle remote manipulator system in four configurations

A possible scenario for robot task performance in space is to mount two small, dexterous arms to the end of the Shuttle Remote Manipulator System (SRMS). As these small robots perform tasks, the flexibility of the SRMS may cause unsuccessful task executions. In order to simulate the dynamic coupling between the SRMS and the arms, admittance models of the SRMS in four brakes locked configurations were developed. The admittance model permits calculation of the SRMS end-effector response due to end-effector disturbing forces. The model will then be used in conjunction with a Stewart Platform, a vehicle emulation system. An application of the admittance model was shown by simulating the disturbing forces using two SRMS payloads, the Dextrous Orbital Servicing System (DOSS) manipulator and DOSS carrying a 1000 lb. cylinder. Mode by mode comparisons were conducted to determine the minimum number of modes required in the admittance model while retaining dynamic fidelity. It was determined that for all four SRMS configurations studied, between 4 and 6 modes of the SRMS structure (depending on the excitation loads) were sufficient to retain tolerance of 0.01 inches and 0.01 deg. These tolerances correspond to the DOSS manipulator carrying no object. When the DOSS carries the 1000 lb. cylinder, between 15 and 20 modes were sufficient, approximately three or four times as many modes as for the unloaded case.

Papadopoulos, Loukas↗

SU-F-J-187: The Statistical NTCP and TCP Models in the Proton Therapy

Purpose: The statistical models (SM) are typically used as a subjective description of a population for which there is only limited sample data, and especially in cases where the relationship between variables is known. The normal tissue complications and tumor control are frequently stochastic effects in the Radiotherapy (RT). Based on probabilistic treatments, it recently has been formulated new NTCP and TCP models for the RT. Investigating the particular requirements for their clinical use in the proton therapy (PT) is the goal of this work. Methods: The SM can be used as phenomenological or mechanistic models. The former way allows fitting real data and getting theirparameters. In the latter one, we should do efforts for determining the parameters through the acceptable estimations, measurements, and/or simulation experiments. Experimental methodologies for determination of the parameters have been developed from the fraction cells surviving the proton irradiation curves in tumor and OAR, and precise RBE models are used for calculating the variable of effective dose. As the executions of these methodologies have a high costs, so we have developed computer tools enable to perform simulation experiments as complement to limitations of the real ones. Results: The requirements for the use of the SM in the PT, such as validation and improvement of the elaborated and existent methodologies for determining the SM parameters and effective dose respectively, were determined. Conclusion: The SM realistically simulates the main processes in the PT, and for this reason these can be implemented in this therapy, which are simples, computable and they have other advantages over some current models. It has been determined some negative aspects for some currently used probabilistic models in the RT, like the LKB NTCP and others derived from logistic functions; which can be improved with the proposed methods in this study.

60 APPLIED LIFE SCIENCES↗

Mission planning and execution within the mission data system

Not only has the number of launched spacecraft per year exploded over the past few years, but also spacecraft are getting progressively more complex, as flyby missions give way to remote orbiters, which in turn give way to rovers and other in situ explorers. To address the software issues in this expanding mission set, JPL started the Mission Data System (MDS) project, an effort to make flight software engineering more straightforward and less prone to error through the eplicit modeling of spacecraft state. This paper presents how MDS performs mission planning and execution in the context of explicitly managing spacecraft state.

MDS↗

MEXEC: An Onboard Integrated Planning and Execution Approach for Spacecraft Commanding

The traditional form of spacecraft commanding is with sequences that specify when commands should execute based on a schedule generated on the ground. Some sequences have control logic and event driven responses to increase flexibility, but it is limited. An approach to increase autonomy is to use goal-based planning and commanding. Using this paradigm, intention and behavior is modeled on board the spacecraft. In this paper we describe MEXEC (Multi-mission EXECutive), a multi-mission, task-based, onboard planning and execution software designed specifically to be used as flight software. As a path to infusion for future flight projects, we describe two experiments performed on the ASTERIA CubeSat and testbed that demonstrate that MEXEC can be integrated and used for spacecraft operations and increase robustness and science return compared to the standard sequences that were being used.

Campuzano, Brian↗

Implementing Arbitrary/Common Concurrent Writes of CRCW PRAM

The Parallel Random Access Machines (PRAM) abstraction is the simplest and most elegant algorithmic model for the design and analysis of parallel algorithms. It consists of different models categorized based on the underlying memory access mode used, the most powerful of which is the Concurrent Read Concurrent Write (CRCW) model. A PRAM algorithm describes a series of rounds, each of which consists of a collection of operations that can be executed concurrently within the same time step. However, the lack of support for concurrent memory accesses and the prevalence of asynchronous programming models led to the belief that implementing CRCW PRAM algorithms is unattainable and prompted many to avoid this model except for theoretical studies of optimal performance.In this work, we study the arbitrary and common concurrent writes in the CRCW PRAM model and explore implementation challenges on general-purpose systems. Moreover, we examine current practices for implementing common/arbitrary concurrent writes and propose a new efficient lightweight and thread-safe method to implement concurrent writes through leveraging atomic instructions. To demonstrate the efficacy of our method, we developed OpenMP kernels for classical CRCW PRAM algorithms and provide experimental results and comparisons based on run time performance measured over the x86 multicore architecture. Our results show a performance speedup compared to current practices up to 4.5x across all our benchmarks.

Ghanim, Fady↗

Uncertainty Quantification and Sensitivity Analysis of Non-Nuclear Advanced Controls Testbed Reactor Mockup

The research presented in this report describes our progress in applying stochastic methods and uncertainty quantification, parametric study, and variance-based sensitivity analysis (also known as Sobol sensitivity analysis) to a full-core model of a nuclear thermal propulsion (NTP) system simulated with Griffin, with the goal of developing a reduced order (surrogate) model which can be rapidly sampled while perturbing multiple input parameters. In this NTP system, reactivity and power feedback affect the rotation of control drums, which are controlled by a hybrid proportional, integral and derivative (PID) controller, actuated by the power demand and reactivity feedback from the numerical model. This model uses reactor kinetic feedback (mean generation time and $\beta$ from a transient Griffin simulation executed with the improved quasi-static method to provide the kinetic parameters) as inputs to functions which control the CD rotation angle. Using a number of stochastic method approaches, we developed a dual purpose training-surrogate model of the NTP system using polynomial regression. The trained model can be rapidly sampled while simultaneously perturbing various input parameters of the model, such as coefficients on the PID control, or temperature (directly affect the neutron cross section). The surrogate model delivers accurate results orders-of-magnitude faster (minutes, not days) than the base model. Once the base model has been trained, distributions of the uncertain parameters can be changed at will to investigate the effects of perturbing multiple inputs and their effect on the output. For example, coefficients used in the PID control system may vary due to some physical interference, or there may be uncertainty in the temperature of the neutron cross sections in various regions of the reactor. A distribution can be placed on these parameters and operational boundaries can be determined. The goal of this work is to support development of an advanced control system to operate CDs in a functioning NTP system.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Temporal Precedence Checking for Switched Models and its Application to a Parallel Landing Protocol

This paper presents an algorithm for checking temporal precedence properties of nonlinear switched systems. This class of properties subsume bounded safety and capture requirements about visiting a sequence of predicates within given time intervals. The algorithm handles nonlinear predicates that arise from dynamics-based predictions used in alerting protocols for state-of-the-art transportation systems. It is sound and complete for nonlinear switch systems that robustly satisfy the given property. The algorithm is implemented in the Compare Execute Check Engine (C2E2) using validated simulations. As a case study, a simplified model of an alerting system for closely spaced parallel runways is considered. The proposed approach is applied to this model to check safety properties of the alerting logic for different operating conditions such as initial velocities, bank angles, aircraft longitudinal separation, and runway separation.

Duggirala, Parasara Sridhar↗

Interactive modeling using the PATRAN-G program

PATRAN-G is an interactive finite element generating and graphics display program. The program is currently executable on the VAX or PRIME computers and is compatible with 19 commercially available graphics terminals. The PATRAN program can be used in two modes: generation of a finite element model, or postprocessing of output data from a finite element analysis program. The finite element generating mode is divided into two phases. Phase I is the geometry construction. During this phase, the geometric boundaries of the model are defined and the material properties are input. Mirror imaging, translation and scaling of lines, surfaces, and volumes, and rotation of regions permit the geometry to be described efficiently. Points may be defined in alternate rectangular, cylindrical, or spherical coordinate systems. Also, PATRAN-G can calculate the intersection of lines or surfaces. This capability allows a user to easily model, for example, the intersection of a cylinder which cuts through a sphere at an angle. Once the geometry of the model has been described in terms of points, lines, surfaces, and volumes. Phase II is used to generate the computer finite element model.

Stalnaker, W. A.↗

NRAP-open-IAM: A flexible open-source integrated-assessment-model for geologic carbon storage risk assessment and management

Large-scale implementation of geologic carbon storage (GCS) to help reduce atmospheric greenhouse gas emissions requires stakeholder confidence that injected CO2 will remain contained and that potential subsurface environmental risks are acceptably small and manageable. The U.S. Department of Energy’s National Risk Assessment Partnership (NRAP) has developed an open-source integrated assessment model (NRAP-Open-IAM) to help address questions about a potential GCS site’s ability to effectively contain injected CO 2 and protect groundwater and other overlying environmentally sensitive receptors. NRAP-Open-IAM allows a user to: (1) incorporate relevant site geologic and injection scenario data; (2) characterize important site features and events;(3) couple fast prediction models of various system components of the engineered geologic system; and (4) execute stochastic, dynamic simulation of whole GCS system performance, leakage risk assessment, and uncertainty quantification. NRAP-Open-IAM is available on GitLab (https://gitlab.com/NRAP/OpenIAM), and is accompanied by multiple application examples and detailed user and developer guides.

54 ENVIRONMENTAL SCIENCES↗

Measurements of Decay and Snapback in Nb₃Sn Accelerator Magnets at Fermilab

In recent years, Fermilab has been executing an inten-sive R&D program on Nb₃Sn accelerator magnets. This program has included dipole and quadrupole models and demonstrators for various programs and projects, including the HL-LHC accelerator upgrade project. A systematic study of the field decay and snapback during the injection portion of a simulated accelerator cycle was executed at the Fermilab Magnet Test Facility. This paper summarizes the recent measurements of the MQXFS1 short quadrupole model and discusses the results of some previously measured Nb₃Sn magnets at CERN

43 PARTICLE ACCELERATORS↗

Information-Theoretic Bounds on Quantum Advantage in Machine Learning

We study the performance of classical and quantum machine learning (ML) models in predicting outcomes of physical experiments. The experiments depend on an input parameter x and involve execution of a (possibly unknown) quantum process E. Our figure of merit is the number of runs of E required to achieve a desired prediction performance. We consider classical ML models that perform a measurement and record the classical outcome after each run of E, and quantum ML models that can access E coherently to acquire quantum data; the classical or quantum data are then used to predict the outcomes of future experiments. We prove that for any input distribution D(x), a classical ML model can provide accurate predictions on average by accessing E a number of times comparable to the optimal quantum ML model. In contrast, for achieving an accurate prediction on all inputs, we prove that the exponential quantum advantage is possible. For example, to predict the expectations of all Pauli observables in an n-qubit system ρ, classical ML models require 2 Ω(n) copies of ρ, but we present a quantum ML model using only O(n) copies. Our results clarify where the quantum advantage is possible and highlight the potential for classical ML models to address challenging quantum problems in physics and chemistry.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Toward Energy-Efficient HPC: Insights from Power Profiling a Cloud-Resolving Earth System Model

Power is a fundamental constraint as supercomputing advances to exascale. Efficient operation within strict power budgets requires application-aware power management based on a detailed understanding of application-level power behavior. This work analyzes the Energy Exascale Earth System Model (E3SM) atmosphere component, SCREAM, on Perlmutter (NERSC) and Frontier (OLCF). We characterize power variation across inputs, concurrency levels, and power caps, evaluate the energy impact of code optimizations, and attribute energy within the code using a newly developed GPU energy model. Results show that SCREAM’s peak power remains stable during its core execution phase and decreases gradually as concurrency increases. Power capping experiments reveal a performance–energy "sweet spot". On Perlmutter, limiting GPU power to 50% of thermal design power (TDP) achieves up to 15% energy savings with a 7% performance penalty. On Frontier, a 40% TDP cap yields up to 10% energy savings with less than 10% performance loss. Code optimizations reduce SCREAM energy by shortening run time without increasing power. Modeling reveals a critical insight: data movement accounts for approximately 70% of SCREAM’s GPU energy. This fundamentally shifts the optimization focus from FLOPS to data transfer reduction for this class of applications, offering the most impactful strategy for improving energy efficiency. This work establishes a foundation for practical, application-aware power management at exascale.

Zhao, Zhengji [Lawrence Berkeley National Laborato↗

2018 Atmospheric Radiation Measurement (ARM) Annual Report

In fiscal year 2018 (FY2018), the Atmospheric Radiation Measurement (ARM) user facility carried out important measurement missions around the globe and worked to better couple ARM measurements with the needs of the science community through the evaluation of priorities and the continued development of new capabilities, including efforts to better link data and models. While many of these efforts have been ongoing, their importance was supported by recommendations from the 2017 ARM Triennial Review. In February 2018, we submitted the final plans to the U.S. Department of Energy (DOE) that ARM will commit to accomplish over the next two years to address the Triennial Review recommendations. We then began implementing activities to: improve and track communications effectiveness at conferences and through the User Executive Committee implement additional metrics to track ARM’s scientific impact, including on model improvement engage users beyond the traditional DOE Office of Biological and Environmental Research (BER)/Atmospheric System Research (ASR) communities increase the timely production and delivery of ARM Mobile Facility value-added products (VAPs) and create a mechanism to better set expectations for VAP delivery to users improve Data Discovery, ARM’s portal for accessing more than 25 years’ worth of data, for users define a clear process for biennially reviewing instrumentation, data products, and other activities with the goal of determining where resources should be applied update the radar plan and create a plan for optimizing aerosol data collection implement operational plans for the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) project and establish a plan for selecting the next science target for LASSO. We have made great progress in all of these areas, much of which is shared in this report, including plans for setting priorities for aerosol measurements and data product development. In FY2018, ARM also brought many plans to fruition that were outlined in its 2014 Decadal Vision strategy, such as the implementation of the LASSO project that integrates observations and models and the continued advancement in the use of unmanned aerial systems (UAS).

MARCUS, POPEYE, Oliktok Point, Eastern North Atlan↗

Enabling Co-Design of Multi-Layer Exascale Storage Architectures

Growing demands for computing power in applications such as energy production, climate analysis, computational chemistry, and bioinformatics have propelled computing systems toward the exascale: systems with 10 18 floating-point operations per second. These systems, to be designed and constructed over the next decade, will create unprecedented challenges in component counts, power consumption, resource limitations, and system complexity. Data storage and access are an increasingly important and complex component in extreme-scale computing systems, and significant design work is needed to develop successful storage hardware and software architectures at exascale. Co-design of these systems will be necessary to find the best possible design points for exascale systems. The goal of this work has been to enable the exploration and co-design of exascale storage systems by providing a detailed, accurate, and highly parallel simulation of exascale storage and the surrounding environment. Specifically, this simulation has (1) portrayed realistic application checkpointing and analysis workloads, (2) captured the complexity, scale, and multilayer nature of exascale storage hardware and software, and (3) executed in a timeframe that enables “what if'” exploration of design concepts. We developed models of the major hardware and software components in an exascale storage system, as well as the application I/O workloads that drive them. We used our simulation system to investigate critical questions in reliability and concurrency at exascale, helping guide the design of future exascale hardware and software architectures. Additionally, we provided this system to interested vendors and researchers so that others can explore the design space. We validated the capabilities of our simulation environment by configuring the simulation to represent the Argonne Leadership Computing Facility Blue Gene/Q system and comparing simulation results for application I/O patterns to the results of executions of these I/O kernels on the actual system.

97 MATHEMATICS AND COMPUTING↗

Group Capability Model

The Group Capability Model (GCM) is a software tool that allows an organization, from first line management to senior executive, to monitor and track the health (capability) of various groups in performing their contractual obligations. GCM calculates a Group Capability Index (GCI) by comparing actual head counts, certifications, and/or skills within a group. The model can also be used to simulate the effects of employee usage, training, and attrition on the GCI. A universal tool and common method was required due to the high risk of losing skills necessary to complete the Space Shuttle Program and meet the needs of the Constellation Program. During this transition from one space vehicle to another, the uncertainty among the critical skilled workforce is high and attrition has the potential to be unmanageable. GCM allows managers to establish requirements for their group in the form of head counts, certification requirements, or skills requirements. GCM then calculates a Group Capability Index (GCI), where a score of 1 indicates that the group is at the appropriate level; anything less than 1 indicates a potential for improvement. This shows the health of a group, both currently and over time. GCM accepts as input head count, certification needs, critical needs, competency needs, and competency critical needs. In addition, team members are categorized by years of experience, percentage of contribution, ex-members and their skills, availability, function, and in-work requirements. Outputs are several reports, including actual vs. required head count, actual vs. required certificates, CGI change over time (by month), and more. The program stores historical data for summary and historical reporting, which is done via an Excel spreadsheet that is color-coded to show health statistics at a glance. GCM has provided the Shuttle Ground Processing team with a quantifiable, repeatable approach to assessing and managing the skills in their organization. They now have a common frame of reference across NASA/contractor lines to communicate and mitigate any critical skills concerns.

Olejarski, Michael↗

Chromosomal integration of complex DNA constructs using CRAGE and CRAGE-Duet systems

Our recent development of the CRAGE (chassis-independent recombinase-assisted genome engineering) system enables single-step integration of large, complex DNA constructs directly into bacteria genomes across multiple phyla. This protocol describes the details of the experimental design and procedures of CRAGE and extended CRAGE-Duet systems. It also describes a strategy that combines CRISPR with CRAGE, which allows implementation of CRISPR-Cas9, CRISPRa, and CRISPRi in diverse bacteria, overcoming major limitations to broaden the application of CRISPR in non-model bacterial genome engineering. For complete details on the use and execution of this protocol, please refer to Wang et al. (2019), Wang et al. (2020), and Liu et al. (2020).

79 ASTRONOMY AND ASTROPHYSICS↗

An Unsteady Actuator Line Solver to Enable Adjoint Sensitivity Studies for Wake Steering

This study demonstrates the sensitivity of wind turbine wake steering performance to blade design. An actuator line model was implemented within an unsteady adjoint solver that enables efficient execution of gradient-based optimization and sensitivity studies. After first confirming the feasibility of wake steering by controlling actuator line chord profiles and formulating a suitable objective function for wake position, a sensitivity study was conducted to determine the relative importance of chord length as a function of spanwise position on the resulting turbine wake deflection. The results presented here support the idea that blade design choices play a role in wake control. In a larger context, this study demonstrates a computational framework in which turbine and blade designs can be studied at the individual and farm-wide level to enhance wind plant controllability and manage power output.

17 WIND ENERGY↗