Managing risk in cost-capped, time-constrained robotic space missions
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project management cost control schedule control↗
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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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Structured prototyping as risk management
A methodology is presented for integrating the systems-engineering management recommendation of prototyping into the traditional project-management process for developing large-scale systems. The suggested methodology begins with the identification of life-cycle risk areas, outlines the structure and conduct of the prototyping process, and defines the composition of the prototyping team. The methodology includes a step-by-step procedure for creating, executing, and documenting a prototyping test plan to evaluate design alternatives. It is argued that managers who adopt this methodology and apply it rigorously will increase the likelihood that the systems they build will be operationally effective and will be accepted by the intended users.
Hornstein, Rhoda SH.↗
Integrating Human Factors into Space Vehicle Processing for Risk Management
This presentation will discuss the multiple projects performed in United Space Alliance's Human Engineering Modeling and Performance (HEMAP) Lab, improvements that resulted from analysis, and the future applications of the HEMAP Lab for risk assessment by evaluating human/machine interaction and ergonomic designs.
Woodbury, Sarah↗
Software risk management through independent verification and validation
Software project managers need tools to estimate and track project goals in a continuous fashion before, during, and after development of a system. In addition, they need an ability to compare the current project status with past project profiles to validate management intuition, identify problems, and then direct appropriate resources to the sources of problems. This paper describes a measurement-based approach to calculating the risk inherent in meeting project goals that leverages past project metrics and existing estimation and tracking models. We introduce the IV&V Goal/Questions/Metrics model, explain its use in the software development life cycle, and describe our attempts to validate the model through the reverse engineering of existing projects.
Callahan, John R.↗
Autonomous, In-Flight Crew Health Risk Management for Exploration-Class Missions: Leveraging the Integrated Medical Model for the Exploration Medical System Demonstration Project
The Integrated Medical Model (IMM) captures organizational knowledge across the space medicine, training, operations, engineering, and research domains. IMM uses this knowledge in the context of a mission and crew profile to forecast risks to crew health and mission success. The IMM establishes a quantified, statistical relationship among medical conditions, risk factors, available medical resources, and crew health and mission outcomes. These relationships may provide an appropriate foundation for developing an in-flight medical decision support tool that helps optimize the use of medical resources and assists in overall crew health management by an autonomous crew with extremely limited interactions with ground support personnel and no chance of resupply.
Butler, D. J.↗
Predicting and Managing Risk to Bats at Commercial Wind Farms using Acoustics
Bat populations in North America face novel threats from white-nose syndrome and widespread turbine-related mortality related to the rapidly expanding wind power industry in addition to long-standing pressures from habitat loss and degradation. Bats, unlike most small mammals, are long-lived and slow to reproduce, highlighting the importance of understanding and managing anthropogenic sources of mortality. My dissertation research used acoustic bat detectors to measure bat activity at commercial wind projects, predict patterns in risk, and design strategic measures to reduce fatality rates by curtailing turbine operation during periods when bats are most active. Bats collide with wind turbines only when their rotors are spinning, and risk of turbine-related fatality is therefore a dynamic factor that can be manipulated by curtailing turbine operation when bats are active. We first measured inter-detector variation in metrics of acoustic bat activity to understand how the acoustic detection process may affect inferences related to spatial and temporal variation in bat activity. Using acoustic detectors mounted on top of wind turbines at two commercial wind farms in West Virginia, we then demonstrated that the amount of bat activity recorded when turbines were operating aligned closely with bat fatality rates on multiple scales. Accordingly, the metric of bat activity exposed to turbine operation provides a meaningful, quantitative indicator of turbine-related bat fatality risk. Further, bats responded consistently to changing wind speed and temperature at turbines in both wind farms across multiple years, enabling exposed bat activity to be predicted accurately among turbines and years. Building on these results, we simulated exposure of bats to turbine operation and energy loss for curtailment strategies recommended by state and federal agencies in the United States and Canada. By adjusting parameters such as cut-in wind speeds and temperature thresholds, we demonstrated the ability to design strategic curtailment programs that achieve equivalent or greater predicted reductions in bat activity exposure for substantially less energy-production loss. Characterizing fatality risk on a finer scale using acoustics will help regulatory agencies and the wind industry alike reduce risks of population-level impacts to vulnerable bat species while continuing to expand large-scale renewable energy generation.
17 WIND ENERGY↗
Defect Detection and Prevention (DDP): A Tool for Failure Mode Risk Management
A principal too under development as part of the NASA Failure Detection and Prevention Program is the Defect Detection and Prevention(DDP) tool.
failure↗
Interplanetary Supply Chain Risk Management
Emphasis on KSC ground processing operations, reduced spares up-mass lift requirements and campaign-level flexible path perspective for space systems support as Regolith-based ISM is achieved by; Network modeling for sequencing space logistics and in-space logistics nodal positioning to include feedstock. Economic modeling to assess ISM 3D printing adaption and supply chain risk.
Galluzzi, Michael C.↗
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.↗
Risk Management of Jettisoned Objects in LEO
The construction and maintenance of the International Space Station (ISS) has led to the release of many objects into its orbital plane, usually during the course of an extra-vehicular activity (EVA). Such releases are often unintentional, but in a growing number of cases, the jettison has been intentional, conducted after a careful assessment of the net risk to the partnership and to other objects in space. Since its launch in 1998 the ISS has contributed on average at least one additional debris object that is simultaneously in orbit with the station, although the number varies widely from zero to eight at any one moment. All of these objects present potential risks to other objects in orbit. Whether it comes from known and tracked orbiting objects or from unknown or untrackable objects, collision with orbital debris can have disastrous consequences. Objects greater than 10cm are generally well documented and tracked, allowing orbiting spacecraft or satellites opportunities to perform evasive maneuvers (commonly known as Debris Avoidance Maneuvers, or DAMs) in the event that imminent collision is predicted. The issue with smaller debris; however, is that it is too numerous to be tracked effectively and yet still poses disastrous consequences if it intercepts a larger object. Due to the immense kinetic energy of any item in orbit, collision with debris as small as 1cm can have catastrophic consequences for many orbiting satellites or spacecraft. Faced with the growing orbital debris threat and the potentially catastrophic consequences of a collision-generated debris shower originating in an orbit crossing the ISS altitude band, in 2007 the ISS program manger asked program specialists to coordinate a multilateral jettison policy amongst the ISS partners. This policy would define the acceptable risk trade rationale for intentional release of a debris object, and other mandatory constraints on such jettisons to minimize the residual risks whenever a jettison was accepted. Although ISS-related debris often presents untenable risks to the EVA crew, IVA crew, or to a departing cargo vehicle for a controlled disposal, such released objects also present a ballistic nuisance to the visiting vehicle traffic, and a potential fragmentation threat to the hundreds of other functional and debris objects whose perigees lie below the ISS orbital altitude. Thus, every such jettison decision is a conscious risk trade.
Bacon, John B.↗
BESS Digital Assurance, Supply Chain Risk Management, and Emerging Regulation Session Two
The TADA BESS Supply Chain Workshops are designed to equip participants with the knowledge and tools necessary to address the evolving challenges at the intersection of battery energy storage systems (BESS), cybersecurity, and supply chain vulnerabilities. The workshops emphasize the application of Cyber-Informed Engineering (CIE) principles using INL’s procurement guide and the CIE-BAT tool. Attendees will develop risk-based security strategies and actionable compliance roadmaps tailored to their BESS projects. Additionally, the program fosters a collaborative network of practitioners and provides guidance on navigating emerging regulatory requirements, including FEOC rules under the OBBB framework, to assess and enhance organizational readiness. A comprehensive exploration of BESS cybersecurity supply chain risks, systematic vendor risk assessment through the BESS Procurement Guide, and practical application of the INL SCRM Chatbot for enhanced supply chain resilience. This is Session 2 of 3. (Full Version)
25 - ENERGY STORAGE↗
BESS Digital Assurance, Supply Chain Risk Management, and Emerging Regulation Session One
The TADA BESS Supply Chain Workshops are designed to equip participants with the knowledge and tools necessary to address the evolving challenges at the intersection of battery energy storage systems (BESS), cybersecurity, and supply chain vulnerabilities. The workshops emphasize the application of Cyber-Informed Engineering (CIE) principles using INL’s procurement guide and the CIE-BAT tool. Attendees will develop risk-based security strategies and actionable compliance roadmaps tailored to their BESS projects. Additionally, the program fosters a collaborative network of practitioners and provides guidance on navigating emerging regulatory requirements, including FEOC rules under the OBBB framework, to assess and enhance organizational readiness. This is Session 1 of 3. (Full Version)
25 - ENERGY STORAGE↗
BESS Digital Assurance, Supply Chain Risk Management, and Emerging Regulation Session One - Abridged
The TADA BESS Supply Chain Workshops are designed to equip participants with the knowledge and tools necessary to address the evolving challenges at the intersection of battery energy storage systems (BESS), cybersecurity, and supply chain vulnerabilities. The workshops emphasize the application of Cyber-Informed Engineering (CIE) principles using INL’s procurement guide and the CIE-BAT tool. Attendees will develop risk-based security strategies and actionable compliance roadmaps tailored to their BESS projects. Additionally, the program fosters a collaborative network of practitioners and provides guidance on navigating emerging regulatory requirements, including FEOC rules under the OBBB framework, to assess and enhance organizational readiness. This is Session 1 of 3.
25 - ENERGY STORAGE↗
Securing Digital Energy Infrastructure: Procurement, Contracting, and Supply Chain Risk Management Guidance
Recognizing the scale of this industry challenge, the United States (U.S.) Department of Energy (DOE) Grid Deployment Office (GDO) and Cybersecurity Energy Security & Emergency Response office have launched a multi-year BESS supply chain security initiative to identify consequence-driven approaches to addressing BESS supply chain security and provide resources to support prioritization of supply chain security efforts associated with the procurement of BESS equipment and services. This guide is one element of the supporting resources to be provided and sets forth a framework and guidance for procurement bidding, selection, risk analysis, and agreements stakeholders can implement to mitigate cybersecurity risks across the entirety of battery system component ecosystem, including the interconnected software and hardware required for control and monitoring BESSs.
25 ENERGY STORAGE↗
Quick Fix for Managing Risks
Under a Phase II SBIR contract, Kennedy and Lumina Decision Systems, Inc., jointly developed the Schedule and Cost Risk Analysis Modeling (SCRAM) system, based on a version of Lumina's flagship software product, Analytica(R). Acclaimed as "the best single decision-analysis program yet produced" by MacWorld magazine, Analytica is a "visual" tool used in decision-making environments worldwide to build, revise, and present business models, minus the time-consuming difficulty commonly associated with spreadsheets. With Analytica as their platform, Kennedy and Lumina created the SCRAM system in response to NASA's need to identify the importance of major delays in Shuttle ground processing, a critical function in project management and process improvement. As part of the SCRAM development project, Lumina designed a version of Analytica called the Analytica Design Engine (ADE) that can be easily incorporated into larger software systems. ADE was commercialized and utilized in many other developments, including web-based decision support.
Source record↗
Mars Sample Return: Risk Management & Sample Safety Assessment
Returning samples from Mars has long been a major planetary science objective due to the high scientific value and transformative potential of the resulting data. An exciting dimension of this objective is the potential for the detection of ancient microbiological life, and the possibility of improving our understanding of the evolution of habitable environments on Mars and the development of life on Earth. To ensure that returned samples meet stringent planetary protection requirements and do not expose Earth to potential biohazards, the joint NASA/ESA Sample Receiving Project (SRP) assembled the Sample Safety Assessment Protocol Tiger Team (SSAP-TT). Members were recruited with the specific goal of creating a multi-disciplinary and internationally distributed team of experts in their respective fields across the federal government, academia, and private industry. This team was chartered with reassessing previous sample safety assessment strategies, defining what constitutes a biological hazard, developing a protocol to test for potential biohazards, and establishing a statistical framework to determine if samples are “safe” for release. The team developed a three-step protocol, supported by a Bayesian statistical framework, to assess whether returned samples contain potential biohazards that could present a risk to Earth’s biosphere. Initial conclusions indicated that an effective and comprehensive safety assessment protocol is feasible using modern techniques and does not require an excessive amount of sample consumption or traditional microbiological detection methodology. Herein, we will present an overview of the MSR SRP, the proposed safety assessment protocol, and how aspects of this novel approach can be applied to biological assessment in healthcare product manufacturing practices.
Alvin L Smith↗
Modular supply chain optimization considering demand uncertainty to manage risk
Supply chain under demand uncertainty has been a challenging problem due to increased competition and market volatility in modern markets. Flexibility in planning decisions makes modular manufacturing a promising way to address this problem. We report the problem of multiperiod process and supply chain network design is considered under demand uncertainty. A mixed integer two-stage stochastic programming problem is formulated with integer variables indicating the process design and continuous variables to represent the material flow in the supply chain. The problem is solved using a rolling horizon approach. Benders decomposition is used to reduce the computational complexity of the optimization problem. To promote risk-averse decisions, a downside risk measure is incorporated in the model. The results demonstrate the several advantages of modular designs in meeting product demands. A pareto-optimal curve for minimizing the objectives of expected cost and downside risk is obtained.
42 ENGINEERING↗