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At least 631 records · Page 35

ASK Talks with Gary Klein

Gary Klein, PH.D., is chief scientist of Klein Associates, Inc., a company he founded in 1978 to better understand how to improve decision making in individuals and teams. The company has 30 employees working on projects for both government and commercial clients. Dr. Klein is one of the founders of the field of naturalistic decision making. His work on recognitional decision making has been influential for the design of new systems and interfaces, and for the development of decision training programs. He has extended his work on decision making to describe problem detection, opinion generation, sense making, and planning.

Klein, Gary↗

Aerospace Engineering Systems

Continuous improvement of aerospace product development processes is a driving requirement across much of the aerospace community. As up to 90% of the cost of an aerospace product is committed during the first 10% of the development cycle, there is a strong emphasis on capturing, creating, and communicating better information (both requirements and performance) early in the product development process. The community has responded by pursuing the development of computer-based systems designed to enhance the decision-making capabilities of product development individuals and teams. Recently, the historical foci on sharing the geometrical representation and on configuration management are being augmented: Physics-based analysis tools for filling the design space database; Distributed computational resources to reduce response time and cost; Web-based technologies to relieve machine-dependence; and Artificial intelligence technologies to accelerate processes and reduce process variability. Activities such as the Advanced Design Technologies Testbed (ADTT) project at NASA Ames Research Center study the strengths and weaknesses of the technologies supporting each of these trends, as well as the overall impact of the combination of these trends on a product development event. Lessons learned and recommendations for future activities will be reported.

VanDalsem, William R.↗

Aerospace Engineering Systems and the Advanced Design Technologies Testbed Experience

Continuous improvement of aerospace product development processes is a driving requirement across much of the aerospace community. As up to 90% of the cost of an aerospace product is committed during the first 10% of the development cycle, there is a strong emphasis on capturing, creating, and communicating better information (both requirements and performance) early in the product development process. The community has responded by pursuing the development of computer-based systems designed to enhance the decision-making capabilities of product development individuals and teams. Recently, the historical foci on sharing the geometrical representation and on configuration management are being augmented: 1) Physics-based analysis tools for filling the design space database; 2) Distributed computational resources to reduce response time and cost; 3) Web-based technologies to relieve machine-dependence; and 4) Artificial intelligence technologies to accelerate processes and reduce process variability. The Advanced Design Technologies Testbed (ADTT) activity at NASA Ames Research Center was initiated to study the strengths and weaknesses of the technologies supporting each of these trends, as well as the overall impact of the combination of these trends on a product development event. Lessons learned and recommendations for future activities are reported.

VanDalsem, William R.↗

Ground Source Heat Pump Screening Tool and Related Resources

This archive contains both a link to Oak Ridge National Laboratory's Ground Source Heat Pump (GSHP) Screening Tool and related resources documenting its development, technical features, and applications. The web-based screening tool is a techno-economic analysis resource designed to evaluate the feasibility, costs, and benefits of implementing GSHP systems in buildings across various U.S. climate zones. It is intended for use by building owners, HVAC system designers, and installers to support decision-making in residential and commercial applications, incorporating advanced modeling capabilities such as ground heat exchanger design. The included resources detail the tool's creation and use, covering topics such as innovative ground heat exchanger design methodologies, the development of an open library of g-functions for borehole configurations, and studies on GSHP performance and economic viability in retrofitting single-family homes.

15 GEOTHERMAL ENERGY↗

Space Launch System Development Status

Development of NASA's Space Launch System (SLS) heavy lift rocket is shifting from the formulation phase into the implementation phase in 2014, a little more than three years after formal program approval. Current development is focused on delivering a vehicle capable of launching 70 metric tons (t) into low Earth orbit. This "Block 1" configuration will launch the Orion Multi-Purpose Crew Vehicle (MPCV) on its first autonomous flight beyond the Moon and back in December 2017, followed by its first crewed flight in 2021. SLS can evolve to a130-t lift capability and serve as a baseline for numerous robotic and human missions ranging from a Mars sample return to delivering the first astronauts to explore another planet. Benefits associated with its unprecedented mass and volume include reduced trip times and simplified payload design. Every SLS element achieved significant, tangible progress over the past year. Among the Program's many accomplishments are: manufacture of Core Stage test panels; testing of Solid Rocket Booster development hardware including thrust vector controls and avionics; planning for testing the RS-25 Core Stage engine; and more than 4,000 wind tunnel runs to refine vehicle configuration, trajectory, and guidance. The Program shipped its first flight hardware - the Multi-Purpose Crew Vehicle Stage Adapter (MSA) - to the United Launch Alliance for integration with the Delta IV heavy rocket that will launch an Orion test article in 2014 from NASA's Kennedy Space Center. Objectives of this Earth-orbit flight include validating the performance of Orion's heat shield and the MSA design, which will be manufactured again for SLS missions to deep space. The Program successfully completed Preliminary Design Review in 2013 and Key Decision Point C in early 2014. NASA has authorized the Program to move forward to Critical Design Review, scheduled for 2015 and a December 2017 first launch. The Program's success to date is due to prudent use of proven technology, infrastructure, and workforce from the Saturn and Space Shuttle programs, a streamlined management approach, and judicious use of new technologies. The result is a safe, affordable, sustainable, and evolutionary path to development of an unprecedented capability for future missions across the solar system. In an environment of economic challenges, the nationwide SLS team continues to meet ambitious budget and schedule targets. This paper will discuss SLS program and technical accomplishments over the past year and provide a look at the milestones and challenges ahead.

Lyles, Garry↗

Human-Autonomy Teaming in a Flight Following Task

The NATO HFM-247 Working Group is creating a summary report of the group's activities on human-autonomy teaming. This chapter is a summary of our at NASA Ames work toward developing a framework for human-autonomy teaming (HAT) in aviation. The purpose of this project was to demonstrate and evaluate proposed tenets of HAT. The HAT features were derived from three tenets and were built into an automated recommender system on a ground station. These tenets include bi-directional communication, automation transparency, and operator directed interface. This study focused primarily on interactions with one piece of automation, the Autonomous Constrained Flight Planner (ACFP). The ACFP is designed to support rapid diversion decisions for commercial pilots in off-nominal situations. Much effort has gone into enhancing this tool not only in capability but also in transparency. In this study, participants used the ACFP at a ground station designed to aid dispatchers in a flight following role to reroute aircraft in situations such as inclement weather, system failures and medical emergencies. Participants performed this task both with HAT features enabled and without and provided feedback. We examined subjective and behavioral indicators of HAT collaborations using a proof-of-concept demonstration of HAT tenets. The data collected suggest potential advantages and disadvantages of HAT.

bi-directional communication↗

Tactical Analysis for Calculating Contextual Risk at Boundaries: Summary of Laboratory Directed Research & Development Effort

The Tactical Analysis for Calculating Contextual Risk at Boundaries (TACCRAB) tool is an innovative digital twin (DT) platform and automated risk algorithm designed to transform operational decision-making in structured screening environments, with an initial focus on Southern Border Land Ports of Entry (POEs). The invention provides integration points for advanced artificial intelligence, predictive modeling, and real-time data analysis to produce a comprehensive risk management tool that enables proactive, data-informed security strategies. The core inventive features of TACCRAB center on its unique risk algorithm, which dynamically calculates contextual risk by synthesizing historical data, near real-time streaming data from the checkpoints themselves, and AI-generated predictions. Unlike traditional risk assessment methods, TACCRAB utilizes a DT to provide comprehensive operational insights, allowing stakeholders to visualize, simulate, and optimize checkpoint configurations with unprecedented speed and contextual awareness. TACCRAB's key innovation lies in its ability to combine multiple complex inputs - including technology detection probabilities, resource availability, screening pathway characteristics, and threat actor behavioral patterns - into a unified risk calculation and update these inputs based on changing operational and environmental conditions. By leveraging a DT that continuously updates and learns from linked data, TACCRAB can suggest adaptive mitigation strategies that minimize risk while maintaining operational efficiency. Particularly novel is the platform's approach to decision support, which goes beyond static risk assessment. The DT provides dynamic metrics such as wait times, resource allocation effectiveness, and potential emerging threat scenarios, enabling users to view sophisticated, relevant what-if simulations and optimize checkpoint operations in near real-time. The system's architecture allows for generalized application across different screening environments, such as secure facilities, ports of entry, and soft targets, making it a versatile tool for security and operational management. The invention distinguishes itself through its comprehensive integration of predictive modeling, AI-driven pattern discovery, and user-friendly interface design. By combining these elements, TACCRAB transforms complex risk data into actionable insights, supporting decision-makers at various organizational levels - from booth agents making split-second screening decisions to checkpoint managers optimizing the day's resource allocation to strategic planners managing long-term investments.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

ISHM Decision Analysis Tool: Operations Concept

The state-of-the-practice Shuttle caution and warning system warns the crew of conditions that may create a hazard to orbiter operations and/or crew. Depending on the severity of the alarm, the crew is alerted with a combination of sirens, tones, annunciator lights, or fault messages. The combination of anomalies (and hence alarms) indicates the problem. Even with much training, determining what problem a particular combination represents is not trivial. In many situations, an automated diagnosis system can help the crew more easily determine an underlying root cause. Due to limitations of diagnosis systems,however, it is not always possible to explain a set of alarms with a single root cause. Rather, the system generates a set of hypotheses that the crew can select from. The ISHM Decision Analysis Tool (IDAT) assists with this task. It presents the crew relevant information that could help them resolve the ambiguity of multiple root causes and determine a method for mitigating the problem. IDAT follows graphical user interface design guidelines and incorporates a decision analysis system. I describe both of these aspects.

Source record↗

Reconfigurable multivariable control law for commercial airplane using a direct digital output feedback design

The ability of a pilot to reconfigure the control surfaces on an airplane after a failure, allowing the airplane to recover to a safe condition for landing, becomes more difficult with increasing airplane complexity. Techniques are needed to stabilize and control the airplane immediately after a failure, allowing the pilot time to make longer range decisions. This paper shows a design of a discrete multivariable control law using four controls for the longitudinal channel of a B-737. Single control element failures are allowed in three of the four controls. The four controls design and failure cases are analyzed by means of a digital airplane simulation, with regard to tracking capability and ability to overcome severe windshear and turbulence during the aproach and landing phase of flight.

Ostroff, A. J.↗

Lunar Equator Regenerative Fuel Cell System Efficiency Analysis

It is expected that future NASA mission energy storage requirements can be adequately met by regenerative fuel cells (RFCs). Aerospace RFCs are likely to package proton exchange membrane electrochemical conversion devices based on hydrogen, oxygen, and water. To optimize system designs and direct further development, the most useful system metric is round-trip efficiency (RTE). Improving RTE generally increases specific energy and reduces system mass. The following analysis models the impact of several factors on RTE for RFCs scaling from 0.1 to 50 kW. The analysis demonstrates that higher electrolyzer (EZ) operational pressure most negatively impacts both RFC RTE and specific energy. Reactant storage heating and power management losses are significant for RFCs of any scale, but solenoid valve power becomes a noticeable parasitic load for smaller RFCs. Spherical gas storage vessels benefit RTE by only 2 to 4 percentage points but increase specific energy by ~50 percent. Cryogenic reactant storage is shown to depress RTE to below 15 percent in all cases. For a given RFC scale, there is an RTE benefit to specifying larger EZs and recharging at higher rates—if the RFC can be coupled with a corresponding power source. Although fuel cell (FC) operation is less impactful on RTE than EZ factors, efficiency is maximized by sizing the FCs relatively large and keeping current density low. RFC design is a balance of many interrelated factors, but this analysis provides a starting point for difficult decisions that must be made when designing a lunar equator RFC.

regenerative fuel cell↗

Lunar South Pole Regenerative Fuel Cell System Efficiency Analysis

It is expected that future NASA mission energy storage needs can be adequately met by regenerative fuel cells (RFCs). Aerospace RFCs package proton exchange membrane (PEM) electrochemical conversion devices based on hydrogen, oxygen, and water. To optimize system designs and direct further development, the most useful system metric is round-trip efficiency (RTE). Improving RTE generally increases specific energy and reduces system mass. The following analysis models the impact of several factors on RTE for RFCs at the lunar south pole scaling from 0.1 kW to 50 kW. The analysis demonstrates that higher electrolyzer operational pressure most negatively impacts both RFC RTE and specific energy. Optimal electrolyzer membrane thickness is evaluated as a function of operational current density and pressure. Reactant storage heating and power management losses are significant for RFCs of any scale but are reduced in impact at the south pole compared to colder equator applications. Solenoid valve power remains a noticeable parasitic load for smaller RFCs. Larger electrolyzers enable higher peak theoretical efficiencies when recharging at higher rates, if the RFC can be coupled with a corresponding higher power source. RFC design is a compromise of many interrelated factors, but this analysis provides a starting point for difficult decisions that must be made when designing a lunar south pole RFC.

regenerative fuel cell↗

Systematic methods for knowledge acquisition and expert system development

Nine cooperating rule-based systems, collectively called AUTOCREW, were designed to automate functions and decisions associated with a combat aircraft's subsystem. The organization of tasks within each system is described; performance metrics were developed to evaluate the workload of each rule base, and to assess the cooperation between the rule-bases. Each AUTOCREW subsystem is composed of several expert systems that perform specific tasks. AUTOCREW's NAVIGATOR was analyzed in detail to understand the difficulties involved in designing the system and to identify tools and methodologies that ease development. The NAVIGATOR determines optimal navigation strategies from a set of available sensors. A Navigation Sensor Management (NSM) expert system was systematically designed from Kalman filter covariance data; four ground-based, a satellite-based, and two on-board INS-aiding sensors were modeled and simulated to aid an INS. The NSM Expert was developed using the Analysis of Variance (ANOVA) and the ID3 algorithm. Navigation strategy selection is based on an RSS position error decision metric, which is computed from the covariance data. Results show that the NSM Expert predicts position error correctly between 45 and 100 percent of the time for a specified navaid configuration and aircraft trajectory. The NSM Expert adapts to new situations, and provides reasonable estimates of hybrid performance. The systematic nature of the ANOVA/ID3 method makes it broadly applicable to expert system design when experimental or simulation data is available.

Belkin, Brenda L.↗

Heuristic decomposition for non-hierarchic systems

Design and optimization is substantially more complex in multidisciplinary and large-scale engineering applications due to the existing inherently coupled interactions. The paper introduces a quasi-procedural methodology for multidisciplinary optimization that is applicable for nonhierarchic systems. The necessary decision-making support for the design process is provided by means of an embedded expert systems capability. The method employs a decomposition approach whose modularity allows for implementation of specialized methods for analysis and optimization within disciplines.

Bloebaum, Christina L.↗

Crew Exploration Vehicle Ascent Abort Overview

One of the primary design drivers for NASA's Crew Exploration Vehicle (CEV) is to ensure crew safety. Aborts during the critical ascent flight phase require the design and operation of CEV systems to escape from the Crew Launch Vehicle and return the crew safely to the Earth. To accomplish this requirement of continuous abort coverage, CEV ascent abort modes are being designed and analyzed to accommodate the velocity, altitude, atmospheric, and vehicle configuration changes that occur during ascent. The analysis involves an evaluation of the feasibility and survivability of each abort mode and an assessment of the abort mode coverage. These studies and design trades are being conducted so that more informed decisions can be made regarding the vehicle abort requirements, design, and operation. This paper presents an overview of the CEV, driving requirements for abort scenarios, and an overview of current ascent abort modes. Example analysis results are then discussed. Finally, future areas for abort analysis are addressed.

Davidson, John B., Jr.↗

Orion Crew Exploration Vehicle Launch Abort System Guidance and Control Analysis Overview

Aborts during the critical ascent flight phase require the design and operation of Orion Crew Exploration Vehicle (CEV) systems to escape from the Crew Launch Vehicle (CLV) and return the crew safely to the Earth. To accomplish this requirement of continuous abort coverage, CEV ascent abort modes are being designed and analyzed to accommodate the velocity, altitude, atmospheric, and vehicle configuration changes that occur during ascent. Aborts from the launch pad to early in the flight of the CLV second stage are performed using the Launch Abort System (LAS). During this type of abort, the LAS Abort Motor is used to pull the Crew Module (CM) safely away from the CLV and Service Module (SM). LAS abort guidance and control studies and design trades are being conducted so that more informed decisions can be made regarding the vehicle abort requirements, design, and operation. This paper presents an overview of the Orion CEV, an overview of the LAS ascent abort mode, and a summary of key LAS abort analysis methods and results.

Davidson, John B.↗

Optimization in the systems engineering process

The objective is to look at optimization as it applies to the design process at a large aircraft company. The design process at Lockheed-Georgia is described. Some examples of the impact that optimization has had on that process are given, and then some areas that must be considered if optimization is to be successful and supportive in the total design process are indicated. Optimization must continue to be sold and this selling is best done by consistent good performance. For this good performance to occur, the future approaches must be clearly thought out so that the optimization methods solve the problems that actually occur during design. The visibility of the design process must be maintained as further developments are proposed. Careful attention must be given to the management of data in the optimization process, both for technical reasons and for administrative purposes. Finally, to satisfy program needs, provisions must be included to supply data to support program decisions, and to communicate with design processes outside of the optimization process. If designers fail to adequately consider all of these needs, the future acceptance of optimization will be impeded.

Lemmerman, L. A.↗

Augmenting Parametric Optimal Ascent Trajectory Modeling with Graph Theory

It has been well documented that decisions made in the early stages of Conceptual and Pre-Conceptual design commit up to 80% of total Life-Cycle Cost (LCC) while engineers know the least about the product they are designing [1]. Once within Preliminary and Detailed design however, making changes to the design becomes far more difficult to enact in both cost and schedule. Primarily this has been due to a lack of detailed data usually uncovered later during the Preliminary and Detailed design phases. In our current budget-constrained environment, making decisions within Conceptual and Pre-Conceptual design which minimize LCC while meeting requirements is paramount to a program's success. Within the arena of launch vehicle design, optimizing the ascent trajectory is critical for minimizing the costs present within such concerns as propellant, aerodynamic, aeroheating, and acceleration loads while meeting requirements such as payload delivered to a desired orbit. In order to optimize the vehicle design its constraints and requirements must be known, however as the design cycle proceeds it is all but inevitable that the conditions will change. Upon that change, the previously optimized trajectory may no longer be optimal, or meet design requirements. The current paradigm for adjusting to these updates is generating point solutions for every change in the design's requirements [2]. This can be a tedious, time-consuming task as changes in virtually any piece of a launch vehicle's design can have a disproportionately large effect on the ascent trajectory, as the solution space of the trajectory optimization problem is both non-linear and multimodal [3]. In addition, an industry standard tool, Program to Optimize Simulated Trajectories (POST), requires an expert analyst to produce simulated trajectories that are feasible and optimal [4]. In a previous publication the authors presented a method for combatting these challenges [5]. In order to bring more detailed information into Conceptual and Pre-Conceptual design, knowledge of the effects originating from changes to the vehicle must be calculated. In order to do this, a model capable of quantitatively describing any vehicle within the entire design space under consideration must be constructed. This model must be based upon analysis of acceptable fidelity, which in this work comes from POST. Design space interrogation can be achieved with surrogate modeling, a parametric, polynomial equation representing a tool. A surrogate model must be informed by data from the tool with enough points to represent the solution space for the chosen number of variables with an acceptable level of error. Therefore, Design Of Experiments (DOE) is used to select points within the design space to maximize information gained on the design space while minimizing number of data points required. To represent a design space with a non-trivial number of variable parameters the number of points required still represent an amount of work which would take an inordinate amount of time via the current paradigm of manual analysis, and so an automated method was developed. The best practices of expert trajectory analysts working within NASA Marshall's Advanced Concepts Office (ACO) were implemented within a tool called multiPOST. These practices include how to use the output data from a previous run of POST to inform the next, determining whether a trajectory solution is feasible from a real-world perspective, and how to handle program execution errors. The tool was then augmented with multiprocessing capability to enable analysis on multiple trajectories simultaneously, allowing throughput to scale with available computational resources. In this update to the previous work the authors discuss issues with the method and solutions.

Patrick D Dees↗

Upgrading Fermilab’s accelerator control system with ACORN

The Fermilab Accelerator Complex is the largest national user facility in the Office of High Energy Physics (DOE/HEP) program and the only national user facility operating at Fermilab. Fermilab serves as the host to the Long Baseline Neutrino Facility/Deep Underground Neutrino Experiment (LBNF/DUNE), the laboratory’s flagship project for neutrino science that is under construction. LBNF/DUNE will be powered by megawatt beams from an upgraded accelerator, the Proton Improvement Plan II (PIP-II) that will replace the laboratory’s aging linear accelerator with a new one based on superconducting radio-frequency cavities. The Accelerator Controls Operations Research Network (ACORN) Project will support LBNF/DUNE and PIP-II by modernizing the accelerator control system. The project is at the conceptual design phase and looking to achieve Critical Decision 1 (CD-1) later this year. The scope and structure of the project will be presented, along with an overview of how that has changed in the past year. Current design and technology choices will be shared. Specific challenges facing the project will be addressed, along with current thinking on solutions.

Roehrig, Christian [Fermilab]↗