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At least 55 records · Page 3

Delivery-Risk-Aware Flexibility Scheduling and Dispatch for Aggregated Flexible Loads

Flexible loads like smart thermostats and water heaters can shift energy consumption and provide flexibility to the grid. However, this flexibility is dependent on occupant behavior and can lead to delivery risk, which causes utilities and grid operations to consider them as unreliable for purposes of grid operation. To date, they have not been well integrated into wholesale electricity markets or ancillary service offerings. With proper consideration of uncertainty and risk, these resources can be one of the most cost-effective sources of flexibility. This work uses stochastic optimization to quantify and bid flexibility from a fleet of flexible resources while considering their delivery risk.

DER↗

Adaptive Independent Verification and Validation (IV&V) Reduces Risk of Software Impacting Safety in Artemis Missions

The National Aeronautics and Space Administration (NASA) is asking more of its human spaceflight programs than ever before through the collective Artemis Missions. The NASA Independent Verification and Validation (IV&V) Program contributes to NASA’s human spaceflight goals by providing IV&V services for NASA’s critical spacecraft and ground software. The IV&V Program is tasked with providing assurance from both individual and integrated mission software perspectives. The Artemis IV&V organization is actively supporting six distinct development efforts: Orion, the Space Launch System (SLS), Exploration Ground Systems (EGS), Mission Control Center (MCC), the Lunar Gateway, and the Human Landing System (HLS), representing a wide diversity of developer organizations, management structures, and development approaches. With much of this extremely complex flight and ground software being essential to human safety both on the ground and in space, Artemis IV&V is likewise challenged to provide more value-added assurance to future Artemis missions within a constrained budget. To meet this challenge, Artemis IV&V employs a variety of novel and evolving “Adaptive IV&V” approaches for planning and executing IV&V analysis to increase both the efficiency and effectiveness of the IV&V Program’s assurance activities, and to address the difficulties imposed by assuring software for a large, highly integrated, multi-mission enterprise managed and executed by physically and organizationally distinct programs. Instilling agile principles like iterative planning cycles, self-organizing teams, and regular retrospectives, into IV&V planning and execution has led to a more rapid turnaround of a minimum viable assurance product and allowed for increased alignment of assurance activities with development progress. Adopting an assurance case methodology has led to greater consistency and clearer communication of assurance design and provided a foundation for long-term maintenance of assurance plans, products, and results across missions. The IV&V-developed Assurance / Safety Case Analytical Network (A-SCAN) framework and tool has enabled the quantification and tracking of system/software risk and confidence. These confidence measures provide a means to repeatedly express the impact of planned and completed assurance work and the remaining residual risk. Applied as part of a “Follow-the-Risk” organizational ethos, this allows consistent rightsizing of analysis rigor and intensity commensurate with the perceived risk of defects, as well as appropriate targeting of the highest risk areas of the software to find safety issues before they can manifest. Finally, the development of the IV&V Advanced Risk Reduction Integrated Software Test and Operations Tri-program Lightweight Environment (ARRISTOTLE), an integrated software-only simulation of Orion, SLS, and EGS systems, has made it possible to independently test integrated pad and flight scenarios and inject faults to observe how the Artemis multi-program, mission software behaves in degraded modes and in response to hazards. These adaptive IV&V investments have enabled Artemis IV&V to become more efficient and effective in IV&V planning and execution and respond more readily to changes in the risk landscape, increasing the breadth and depth of risk reduction possible within the available resources. Residual risk tracking allows IV&V to communicate more effectively with stakeholders, both internal and external at all levels, and inform key decision-making personnel. This evolving assurance design approach provides IV&V surety that work is performed in the highest risk, most value-added areas of the software, to keep our astronauts and ground crews safe and ensure mission success.

Gerek A Whitman↗

Adaptive Independent Verification and Validation (IV&V) Reduces Risk of Software Impacting Safety in Artemis Missions

The National Aeronautics and Space Administration (NASA) is asking more of its human spaceflight programs than ever before through the collective Artemis Missions. The NASA Independent Verification and Validation (IV&V) Program contributes to NASA’s human spaceflight goals by providing IV&V services for NASA’s critical spacecraft and ground software. The IV&V Program is tasked with providing assurance from both individual and integrated mission software perspectives. The Artemis IV&V organization is actively supporting six distinct development efforts: Orion, the Space Launch System (SLS), Exploration Ground Systems (EGS), Mission Control Center (MCC), the Lunar Gateway, and the Human Landing System (HLS), representing a wide diversity of developer organizations, management structures, and development approaches. With much of this extremely complex flight and ground software being essential to human safety both on the ground and in space, Artemis IV&V is likewise challenged to provide more value-added assurance to future Artemis missions within a constrained budget. To meet this challenge, Artemis IV&V employs a variety of novel and evolving “Adaptive IV&V” approaches for planning and executing IV&V analysis to increase both the efficiency and effectiveness of the IV&V Program’s assurance activities, and to address the difficulties imposed by assuring software for a large, highly integrated, multi-mission enterprise managed and executed by physically and organizationally distinct programs. Instilling agile principles like iterative planning cycles, self-organizing teams, and regular retrospectives, into IV&V planning and execution has led to a more rapid turnaround of a minimum viable assurance product and allowed for increased alignment of assurance activities with development progress. Adopting an assurance case methodology has led to greater consistency and clearer communication of assurance design and provided a foundation for long-term maintenance of assurance plans, products, and results across missions. The IV&V-developed Assurance / Safety Case Analytical Network (A-SCAN) framework and tool has enabled the quantification and tracking of system/software risk and confidence. These confidence measures provide a means to repeatedly express the impact of planned and completed assurance work and the remaining residual risk. Applied as part of a “Follow-the-Risk” organizational ethos, this allows consistent rightsizing of analysis rigor and intensity commensurate with the perceived risk of defects, as well as appropriate targeting of the highest risk areas of the software to find safety issues before they can manifest. Finally, the development of the IV&V Advanced Risk Reduction Integrated Software Test and Operations Tri-program Lightweight Environment (ARRISTOTLE), an integrated software-only simulation of Orion, SLS, and EGS systems, has made it possible to independently test integrated pad and flight scenarios and inject faults to observe how the Artemis multi-program, mission software behaves in degraded modes and in response to hazards. These adaptive IV&V investments have enabled Artemis IV&V to become more efficient and effective in IV&V planning and execution and respond more readily to changes in the risk landscape, increasing the breadth and depth of risk reduction possible within the available resources. Residual risk tracking allows IV&V to communicate more effectively with stakeholders, both internal and external at all levels, and inform key decision-making personnel. This evolving assurance design approach provides IV&V surety that work is performed in the highest risk, most value-added areas of the software, to keep our astronauts and ground crews safe and ensure mission success.

Gerek Whitman↗

MEDPRAT-SEL: Medical Resource Set Selector Searching High-Dimensionality Space

NASA Human Research Program's (HRP) next generation risk model closes the loop on medical risk and resource evaluation, providing researchers with a tool to assess and choose capabilities scientifically. The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) simulator (SIM) evaluates resources in terms of medical benefit, such as reduced crew quality time lost (QTL), vs. cost, in mass or volume. The MEDPRAT resource set selector (SEL) searches the space of resource benefits v. cost, closing a feedback loop around the simulator, thus selecting resource sets with best benefit for cost. We discuss the design and results of the resource set selector. NASA HRP's emphasis on scientific assessment of risk, PRA, has led to the Cross-cutting Computational Modeling Project (CCMP).

Leinweber, Lawrence↗

Risk management for the Space Exploration Initiative

Probabilistic Risk Assessment (PRA) is a quantitative engineering process that provides the analytic structure and decision-making framework for total programmatic risk management. Ideally, it is initiated in the conceptual design phase and used throughout the program life cycle. Although PRA was developed for assessment of safety, reliability, and availability risk, it has far greater application. Throughout the design phase, PRA can guide trade-off studies among system performance, safety, reliability, cost, and schedule. These studies are based on the assessment of the risk of meeting each parameter goal, with full consideration of the uncertainties. Quantitative trade-off studies are essential, but without full identification, propagation, and display of uncertainties, poor decisions may result. PRA also can focus attention on risk drivers in situations where risk is too high. For example, if safety risk is unacceptable, the PRA prioritizes the risk contributors to guide the use of resources for risk mitigation. PRA is used in the Space Exploration Initiative (SEI) Program. To meet the stringent requirements of the SEI mission, within strict budgetary constraints, the PRA structure supports informed and traceable decision-making. This paper briefly describes the SEI PRA process.

Buchbinder, Ben↗

NASA Propulsion Sub-System Concept Studies and Risk Reduction Activities for Resource Prospector Lander

NASA's exploration roadmap is focused on developing technologies and performing precursor missions to advance the state of the art for eventual human missions to Mars. One of the key components of this roadmap is various robotic missions to Near-Earth Objects, the Moon, and Mars to fill in some of the strategic knowledge gaps. The Resource Prospector (RP) project is one of these robotic precursor activities in the roadmap. RP is a multi-center and multi-institution project to investigate the polar regions of the Moon in search of volatiles. The mission is rated Class D and is approximately 10 days, assuming a five day direct Earth to Moon transfer. Because of the mission cost constraint, a trade study of the propulsion concepts was conducted with a focus on available low-cost hardware for reducing cost in development, while technical risk, system mass, and technology advancement requirements were also taken into consideration. The propulsion system for the lander is composed of a braking stage providing a high thrust to match the lander's velocity with the lunar surface and a lander stage performing the final lunar descent. For the braking stage, liquid oxygen (LOX) and liquid methane (LCH4) propulsion systems, derived from the Morpheus experimental lander, and storable bi-propellant systems, including the 4th stage Peacekeeper (PK) propulsion components and Space Shuttle orbital maneuvering engine (OME), and a solid motor were considered for the study. For the lander stage, the trade study included miniaturized Divert Attitude Control System (DACS) thrusters (Missile Defense Agency (MDA) heritage), their enhanced thruster versions, ISE-100 and ISE-5, and commercial-off-the-shelf (COTS) hardware. The lowest cost configuration of using the solid motor and the PK components while meeting the requirements was selected. The reference concept of the lander is shown in Figure 1. In the current reference configuration, the solid stage is the primary provider of delta-V. It will generate 15,000-lbf of thrust with a single burn of ~ 80's seconds. The lander stage is a bi-propellant, pressure-regulated, pulsing liquid propulsion system to perform all other functions.

Trinh, Huu P.↗

NASA Propulsion Concept Studies and Risk Reduction Activities for Resource Prospector Lander

The Resource Prospector mission is to investigate the Moon's polar regions in search of volatiles. The government-version lander concept for the mission is composed of a braking stage and a liquid-propulsion lander stage. A propulsion trade study concluded with a solid rocket motor for the braking stage while using the 4th-stage Peacekeeper (PK) propulsion components for the lander stage. The mechanical design of the liquid propulsion system was conducted in concert with the lander structure design. A propulsion cold-flow test article was fabricated and integrated into a lander development structure, and a series of cold flow tests were conducted to characterize the fluid transient behavior and to collect data for validating analytical models. In parallel, RS-34 PK thrusters to be used on the lander stage were hot-fire tested in vacuum conditions as part of risk reduction activities.

Trinh, Huu P.↗

Development and Application of a Risk Analysis Toolkit for Plant Resources Optimization

This report summarizes the R&D activities of the Risk Informed Asset Management (RIAM) project during fiscal year 2020 (FY20). This project focuses on the development of methods designed to optimize plant operations (e.g., maintenance/replacement schedule, optimal maintenance posture) provided system/component health/cost data. This project development lives in cooperation with the Plant Health Management (PHM) project which focuses on the development of methods that integrate component health data and propagate such information at the system level to evaluate most relevant sources of risk. This year’s activities for the RIAM project focused on the continuation of schedule optimization algorithms developed in FY19. While in FY19 we focused on both deterministic and stochastic capital budgeting methods, in FY20 we moved forward by implementing two versions of schedule optimization methods. The first one reformulates the capital budgeting problem in a distributionally robust form which allows the user to rely on data directly rather than proposing a distribution from the data itself. The second version reformulates the capital budgeting explicitly using risk measures as variables to maximize/minimize. Lastly, we focused on the development of methods designed to identify the optimal maintenance posture based on the Pareto Frontier analysis. Rather than performing a tradeoff analysis (i.e., identify the absolute best posture), the Pareto Frontier analysis performs a trade space exploration approach (i.e., identify value and costs of several postures and have the analyst perform the task of imposing desired value and cost constraints). This is performed by identifying maintenance postures that maximize value (e.g., system availability) and minimize operational costs, i.e., the Pareto frontier in a value-cost trade space.

97 MATHEMATICS AND COMPUTING↗

New Resource Adequacy Criteria for the Energy Transition: Modernizing Reliability Requirements

The transition toward a cleaner and more weather-dependent power system brings with it unprecedented challenges and opportunities for maintaining resource adequacy—namely, a future that includes rapid load growth, plant retirements, and a shift toward variable and energy-limited resources. Resource adequacy analyses, capacity accreditation, and the resource adequacy planning criteria are becoming increasingly important for power system planning and investment decisions. While previous ESIG reports evaluated the changing resource adequacy risks and planning practices created by the energy transition, none specifically examined potential changes to the resource adequacy criterion used for planning. The resource adequacy criterion sets the level of supply- and demand-side resources that are required for a given power system to meet reliability objectives. It is a pivotal standard that influences billions of dollars of investment decisions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Electricity Rate Designs for Large Loads: Evolving Practices and Opportunities

Electricity demand from large load customers such as data centers is projected to grow significantly in the near term. While data centers play an important role in advancing technology innovation and economic growth in the United States, data center energy needs present challenges and opportunities for electricity supply and infrastructure. This technical brief serves as a foundation for the discussion of issues and sharing of perspectives among utilities, regulators, large load customers, and other stakeholders. As utilities and regulators explore rate structures to address growing data center electricity demand, several issues have emerged: -Fair allocation of electricity system costs to large-load customers without unfair shifting of costs to other customers -Appropriate mitigation of the financial risks associated with stranded assets from underutilized utility system investments -Mitigation of operational and resource adequacy risks if electricity demand exceeds supply -Appropriate risk-sharing in commercializing newer electricity technologies such as advanced geothermal, small modular reactors, and long duration energy storage -Accommodating the diverse needs of large-load customers, such as having the option to match electricity consumption with output from carbon-free resources or using onsite generation to provide system capacity The technical brief also identifies key design elements that aim to address these issues and uses leading examples from pending and approved rate structures, agreements, and special contracts to ground the elements in practice.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Medical Resource Set Bulky Item Trade Space Analysis for Spaceflight Medical Risk

The NASA engineering community utilizes event-driven and fault-tree probabilistic techniques to classify risks in the space environment by taking advantage of the inherent knowledge of complex spaceflight system design and testing to quantify failure risk. In harmonizing the risk of human space flight, answering the question of ‘How do we balance health, performance and resource risks with other engineering risks on long duration space missions?’ remains a deeply challenging and largely qualitative practice. The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) is one aspect of the efforts by NASA’s Human Research Program (HRP) to quantitatively assess the impact of health and performance risk. One of MEDPRAT’s key features is its high degree of computational efficiency. Coupled with the HRP High Performance Compute cluster located at NASA’s Glenn Research Center, MEDPRAT runs millions of simulated missions in a matter of minutes. This degree of computational efficiency provides the novel opportunity to explore the relationship between medical set mass, volume, and medical resource size. Of particular interest for future human spaceflight missions are ‘bulky’ items, medical resources like devices, which occupy a large portion of the small, allocated mass and volume for the medical set leaving less room for other resources. This talk will present results showing the quantitative impact of forced inclusion of several bulky items across a variety of medical kit constraints, and the effect that a potential research investment into reducing the bulky item mass and volume may have on risk.

Lauren Mcintyre↗

Dual Impacts of Space Heating Electrification and Climate Change Increase Uncertainties in Peak Load Behavior and Grid Capacity Requirements in Texas

Around 60% of households in Texas currently rely on electricity for space heating. As decarbonization efforts increase, non‐electrified households could adopt electric heat pumps, significantly increasing peak (highest) electricity demand in winter. Simultaneously, anthropogenic climate change is expected to increase temperatures, the potential for summer heat waves, and associated electricity demand for cooling. Uncertainty regarding the timing and magnitude of these concurrent changes raises questions about how they will jointly affect the seasonality of peak demand, firm capacity requirements, and grid reliability. This study investigates the net effects of residential space heating electrification and climate change on long‐term demand patterns and load shedding potential, using climate change projections, a predictive load model, and a direct current optimal power flow (DCOPF) model of the Texas grid. Results show that full electrification of residential space heating by replacing existing fossil fuel use with higher efficiency heat pumps could significantly improve reliability under hotter futures. Less efficient heat pumps may result in more severe winter peaking events and increased reliability risks. As heating electrification intensifies, system planners will need to balance the potential for greater resource adequacy risk caused by shifts in seasonal peaking behavior alongside the benefits (improved efficiency and reductions in emissions).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Target Diagnostic Menu Lawrence Livermore National Laboratory SYSM-5620: Design Thinking and Systems Engineering

Target Diagnostic’s Engineering Science (TDES) currently supports over 80 diagnostic systems, all of which draw from a fixed budget that covers staff time and procurement. As the division continues to add new diagnostics, demand on these limited resources increases, yet the budget remains unchanged. Shot Responsible Individuals (RIs) have unrestricted freedom to select any number or type of diagnostics for each experiment, often by copying previous shot configurations with only minor modifications. This practice makes it easy to generate new shots but does not encourage critical evaluation of diagnostic necessity. As a result, many diagnostics are routinely included in a shot without a clear justification, and in practice, much of the data collected is not analyzed. The ever-growing arsenal of diagnostics also increases the burden on TDES personnel, requiring more staff for support, maintenance, and service. This environment creates challenges in focusing resources on diagnostics that provide the greatest value to the NIF mission and raises concerns about the continued justification for maintaining all existing systems. The static TDES budget cannot sustain the ongoing growth in demand for new diagnostic systems. Shot RIs currently face no constraints on the number or type of diagnostics they assign to each experiment, often defaulting to previous configurations without critically assessing the necessity of each diagnostic. This results in the routine inclusion of diagnostics whose data may not be analyzed or may no longer directly support the NIF mission. Consequently, TDES is required to maintain and support an expanding set of diagnostics, straining limited resources and risking inefficient use of staff and funding. There is a need for TDES to efficiently allocate limited resources by establishing a process that requires shot RIs to critically evaluate and justify the inclusion of each diagnostic in their experiments. This process should discourage the routine, unexamined inclusion of diagnostics, support the identification of underutilized or obsolete systems, and ensure that only those diagnostics providing the greatest value to the NIF mission are maintained and supported. Ultimately, this approach must enable TDES to operate within budget constraints while maximizing scientific impact and operational efficiency.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Flexibility Auctions: A Framework for Managing Imbalance Risk

As the electricity generated by variable resources grows, system operators and variable resources have to manage challenging imbalances between forward and real-time markets. The Flexibility Auction is a novel approach for managing imbalances as it will allow resources with imbalance risk to hedge their production by buying flexibility options. The flexibility options are offered by grid-connected resources that can provide physical flexibility. This presentation will focus on the design of the Flexibility Auction, its properties, and how it can complement system-level services such as CAISO's proposed imbalance reserves. The presentation will include simple examples to illustrate the impact of the Flexibility Auction on the market participants and the system's imbalance risk.

auction↗

Flexibility Options: A Proposed ISO Product for Managing Energy Imbalance Risk

As the electricity generated by variable resources grows, system operators and variable resources have to manage challenging imbalances between forward and real-time markets. The Flexibility Auction is a novel approach for managing imbalances as it will allow resources with imbalance risk to hedge their production by buying flexibility options. The flexibility options are offered by grid-connected resources that can provide physical flexibility. This presentation provides an overview of the participants in the auction, the definition of flexibility options, and settlements.

27 ARPA - Advanced Research Projects Agency-Energy↗

Improving the Fidelity of Capability & Resource Weighting in A Probalistic Risk Assessment Model for Spaceflight

INTRODUCTION NASA’s Informing Mission Planning via Analysis of Complex Tradespaces (IMPACT) tool uses Probabilistic Risk Assessment (PRA) to provide an evidence-based, data-driven estimate of how medical system capabilities affect mission outcomes. IMPACT maps condition incidence to available resources thereby facilitating the calculation of outcome metrics that allow the estimation of mission medical risk. Conditions can be nominally categorized as either treated or untreated depending on the availability of necessary diagnostic and therapeutic capabilities. This categorization enables IMPACT to estimate the effect of various medical system configurations on mission outcomes such as crew mortality, disability, crew member down-time, return to duty/recovery, and need for evacuation. IMPACT currently employs an equal weighting, “partial credit” approach to define treatment in which each of the capabilities associated with a given condition contributes an equal amount to management of the condition. This feature enables IMPACT to report values in between “fully untreated” and “fully treated” based on the proportion of capabilities available within the model. However, as is normal in medical/clinical practice, not all individual capabilities contribute equally to medical care. For example, the ability to provide intramuscular epinephrine during an anaphylactic episode contributes more likelihood of overall management success than does the administration of oral diphenhydramine. We hypothesize that weighting the relative contribution of each capability to each specific condition will improve outcome prediction and therefore will better provide mission planners with more nuanced and accurate options when designing space medical systems. METHODS Using a five-point Fibonacci scaling sequence (1, 2, 3, 5, 8) subject matter experts from NASA’s Exploration Medical Capabilities (ExMC) element assigned relative contribution weighting values to each identified capability within IMPACT. Since the relative importance of each capability varies depending on the specific condition, the resulting “partial” weighting was completed for more than 1,600 individual weighting assignments for 666 capabilities across 121 conditions. Each assignment required three-physician concurrence based on the overall importance of the capability to the diagnosis and management of the condition being considered and the difficulty with which it could be improvised by the crew. Once complete, 100,000 IMPACT simulations were run for a 6-month Lunar mission with a 30-day surface stay to evaluate the effect of this modification of the model. RESULTS Partial weighting significantly decreased predicted task time loss (TTL), evacuation, and loss of crew life without causing significant changes to the recommended medical system design. CONCLUSIONS The paucity of real-world referent data to support long-duration space missions of this type limits the ability to judge one predictive analytics method as superior to another. However, since the proposed method significantly reduces and optimizes outcome risks—without changing the medical system design—incorporating a partial weighting methodology is likely to provide a more accurate and operationally-relevant representation of medical risk without compromising IMPACTs ability to inform overarching medical system requirements.

Steller JG↗

Risk-Averse Bi-Level Stochastic Network Interdiction Model for Cyber-Security Risk Management

Security of cyber networks is crucial; recent severe cyber-attacks have had a devastating effect on many large organizations. The attack graph, which maps the potential attack paths of a cyber network, is a popular tool for analyzing cyber system vulnerability. In this study, we propose a bi-level stochastic network interdiction model on an attack graph to enable a risk-averse, resource constrained cyber network defender to optimally deploy security countermeasures that protect against attackers with an uncertain budget. This risk- averse conditional-value-at-risk (CVaR) model minimizes a weighted sum of the expected maximum loss over all scenarios and the expected maximum loss from the most damaging attack scenarios. We develop a customized constraint and column generation algorithm to solve our model as well as several acceleration techniques to improve the computational efficiency. Numerical experiments demonstrate that the acceleration techniques enable the solution of relatively large problems within a reasonable amount of time: applying all the acceleration techniques also reduces the average computation time of the basic algorithm by 71% for 100-node graphs. Using metrics called mean-risk value of stochastic solution and value of risk-aversion, computational results suggest that our stochastic risk-averse model significantly outperforms deterministic and risk-neutral models when 1) the distribution of attacker budget is heavy-right-tailed and 2) the defender is highly risk-averse.

Bhuiyan, Tanveer H.↗

Wind Tunnel Management and Resource Optimization: A Systems Modeling Approach

Time, money, and, personnel are becoming increasingly scarce resources within government agencies due to a reduction in funding and the desire to demonstrate responsible economic efficiency. The ability of an organization to plan and schedule resources effectively can provide the necessary leverage to improve productivity, provide continuous support to all projects, and insure flexibility in a rapidly changing environment. Without adequate internal controls the organization is forced to rely on external support, waste precious resources, and risk an inefficient response to change. Management systems must be developed and applied that strive to maximize the utility of existing resources in order to achieve the goal of "faster, cheaper, better". An area of concern within NASA Langley Research Center was the scheduling, planning, and resource management of the Wind Tunnel Enterprise operations. Nine wind tunnels make up the Enterprise. Prior to this research, these wind tunnel groups did not employ a rigorous or standardized management planning system. In addition, each wind tunnel unit operated from a position of autonomy, with little coordination of clients, resources, or project control. For operating and planning purposes, each wind tunnel operating unit must balance inputs from a variety of sources. Although each unit is managed by individual Facility Operations groups, other stakeholders influence wind tunnel operations. These groups include, for example, the various researchers and clients who use the facility, the Facility System Engineering Division (FSED) tasked with wind tunnel repair and upgrade, the Langley Research Center (LaRC) Fabrication (FAB) group which fabricates repair parts and provides test model upkeep, the NASA and LARC Strategic Plans, and unscheduled use of the facilities by important clients. Expanding these influences horizontally through nine wind tunnel operations and vertically along the NASA management structure greatly increases the complexity of developing a model that can be used for successfully implementing a standardized management planning tool. The objective of this study was to implement an Integrated Wind Tunnel Planning System to improve the operations within the aeronautics testing and research group, in particular Wind Tunnel Enterprise. The study included following steps: Conducted literature search and expert discussions (NASA and Old Dominion University faculty), Performed environmental scan of NASA Langley wind tunnel operations as foundation for problem definition. Established operation requirements and evaluation methodologies. Examined windtunnel operations to map out the common characteristics, critical components, and system structure. Reviewed and evaluated various project scheduling and management systems for implementation, Evaluated and implemented "Theory of Constraints (TOC)" project scheduling methodology at NASA Langley wind tunnel operations together with NASA staff.

Jacobs, Derya, A.↗