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NASA NTRS2016

Cost-Benefit Analysis for the Advanced Near Net Shape Technology (ANNST) Method for Fabricating Stiffened Cylinders

Low Technology Readiness Levels (TRLs) and high levels of uncertainty make it challenging to develop cost estimates of new technologies in the R&D phase. It is however essential for NASA to understand the costs and benefits associated with novel concepts, in order to prioritize research investments and evaluate the potential for technology transfer and commercialization. This paper proposes a framework to perform a cost-benefit analysis of a technology in the R&D phase. This framework was developed and used to assess the Advanced Near Net Shape Technology (ANNST) manufacturing process for fabricating integrally stiffened cylinders. The ANNST method was compared with the conventional multi-piece metallic construction and composite processes for fabricating integrally stiffened cylinders. Following the definition of a case study for a cryogenic tank cylinder of specified geometry, data was gathered through interviews with Subject Matter Experts (SMEs), with particular focus placed on production costs and process complexity. This data served as the basis to produce process flowcharts and timelines, mass estimates, and rough order-of-magnitude cost and schedule estimates. The scalability of the results was subsequently investigated to understand the variability of the results based on tank size. Lastly, once costs and benefits were identified, the Analytic Hierarchy Process (AHP) was used to assess the relative value of these achieved benefits for potential stakeholders. These preliminary, rough order-of-magnitude results predict a 46 to 58 percent reduction in production costs and a 7-percent reduction in weight over the conventional metallic manufacturing technique used in this study for comparison. Compared to the composite manufacturing technique, these results predict cost savings of 35 to 58 percent; however, the ANNST concept was heavier. In this study, the predicted return on investment of equipment required for the ANNST method was ten cryogenic tank barrels when compared with conventional metallic manufacturing. The AHP study results revealed that decreased final cylinder mass and improved quality assurance were the most valued benefits of cylinder manufacturing methods, therefore emphasizing the relevance of the benefits achieved with the ANNST process for future projects.

Ivanco, Marie L.↗

NASA NTRS2019

Quantifying the Impact of Systems Interdependencies in Space Systems Architectures

Due to the high number of systems in a space mission architecture and to their complex interactions, identifying risk and critical operational dependencies is not obvious. Traditional systems engineering methodology and risk assessment does not capture the impact of interactions between systems nor the cascading effects of disruptions. Based on these considerations, the Systems Operational Dependency Analysis methodology was developed for use by systems analysts and decision makers. This methodology utilizes a parametric model of interdependencies between systems to quantify the direct and indirect impact of system disruptions on other systems, as well as identify root causes. The results are effective at providing decision support for prioritizing technology investment based on risk reduction associated with potential system disruptions. Expanding on research presented at IAC 2018 and based on a collaboration with NASA Marshall Space Flight Center, this paper applies the Systems Operational Dependency Analysis methodology to NASA Lunar Gateway in collaboration with NASA’s lunar exploration plans. The paper presents a hierarchical representation of the interdependencies between a Gateway habitat’s systems and subsystems, demonstrates quantification of the impact of disruption, and assesses the criticality of the constituent systems and subsystems.

Guariniello, Cesare↗

NASA NTRSDate not supplied

NASA Crew Health & Performance Capability Development for Exploration: 2022 to 2023 Overview

Radiation, reduced gravity, distance from earth, isolation and confinement, and habitation within artificially created and controlled life support environments are hazards that present risk to human space explorers. These hazards necessitate development of new technologies to protect crew health and performance during future long-duration missions to the moon and Mars. NASA’s System Capability Leads coordinate with agency experts, programs, and exploration architecture teams to identify and prioritize technology investments in support of future missions. This paper describes progress over the past year in CHP technology development, ground testbed development, ground-based testing, and in-flight technology demonstrations. Technology maturation progress and future plans are described in the following capability areas: crew health countermeasures; spacesuit physiology and performance; food and nutrition; radiation protection; and exploration medical capabilities.

Andrew F.J. Abercromby↗

NASA NTRSDate not supplied

NASA Avionics Technology Shortfalls

NASA’s Space Technology Mission Directorate (STMD) leads the development, demonstration, and infusion of transformational technologies that enhance NASA’s efforts to explore the unknown in space, benefit life on Earth, and solve critical stakeholder needs. STMD is refining its strategy for prioritizing technology investments, with the goal of evolving into a stronger and more resilient national tech base for civil space.

Wesley Powell↗

DOE OSTI2020

APPLICATION OF MATURITY MODELS FOR EVALUATING CYBERSECURITY PROGRAMS AT NUCLEAR AND RADIOLOGICAL FACILITIES

Maturity models can be used to provide government agencies, industry associations, and organizations operating nuclear facilities with the ability to quickly evaluate the maturity of their cybersecurity programs and identify areas to prioritize for improvement. The Cybersecurity Capability Maturity Model (C2M2) was developed by the U.S. Department of Energy to allow organizations in the energy sector to evaluate the programmatic capabilities of their cybersecurity programs in a consistent manner, communicate programmatic maturity information, prioritize cybersecurity investments in targeted areas of concern, and track how the maturity of their cybersecurity program evolves over time. The C2M2 is designed for use by any critical infrastructure organization regardless of ownership, structure, or size. The C2M2 can be easily fine-tuned to access the maturity of nuclear cybersecurity programs and their application at individual facilities. Built on a foundation of existing cybersecurity standards, frameworks, programs, and initiatives, the model features 10 security domains. Performance in each security domain is characterized using a structured set of cybersecurity practices that represent activities an organization can perform to improve cybersecurity in their domain. Each practice can be quickly evaluated as being either fully, largely, partially, or not implemented. Once practices are evaluated for each security domain, the model defines four maturity indicator levels that apply independently to each domain in the model. To earn a maturity level in a given domain, an organization must adequately perform all the practices for that maturity level and its predecessor level(s). A small assessment team can conduct a C2M2 assessment in a single day. A screening version of the C2M2 allows an initial look at the maturity of nuclear cybersecurity programs that could be completed in under an hour.

Cyber security, Nuclear security, maturity model↗

NASA NTRS2000

Satellite Broadcast of Graphical Weather Data Flight Tested

NASA Glenn Research Center at Lewis Field's aviation Weather Information Communications (WINCOMM) and NASA Langley Research Center's Aviation Weather Information (AWIN) programs collaborated in a flight test and evaluation of a worldwide weather data-link capability using satellites. This successful flight testing moves NASA closer to its goal of developing advanced communications and information technologies to enable high-quality and timely dissemination of aviation weather information to all relevant users on the aviation information network. Recognized as a major contributing factor in aviation accidents and incidents, weather contributes directly or indirectly to nearly 80 percent of fatal general aviation (small private aircraft) accidents. In 1997, the Aeronautics Safety Investment Strategy Team s weather team produced a prioritized list of investment areas under weather accident prevention. Weather data dissemination is the most critical and highest ranked priority on the list. NASA's Aviation Safety Program founded the Aviation Weather Information initiative to focus efforts on significantly reducing the number of weather-related aviation fatalities. Access to accurate and timely weather data could contribute to a major reduction of weather-related incidents and accidents. However, a cost-effective solution has eluded most general aviation pilots because of the high cost of onboard weather radar equipment. Rockwell Collins, through a contract with NASA and in cooperation with WorldSpace Corporation, successfully completed ground and flight testing of a receiver and antenna in Johannesburg, South Africa. This NASA/Rockwell Collins project is an evaluation of worldwide weather data-link capability using transmissions from the Satellite Digital Audio Radio Services (S DARS) AfriStar satellite. Owned and operated by WorldSpace, AfriStar is a geostationary satellite that broadcasts commercial digital audio services to stationary and mobile platforms. S DARS satellites are the most powerful communications satellites produced to date, allowing users to receive signals using simple, low-cost patch antennas instead of more expensive, beam-steered antenna arrays. Engineers connected an inexpensive, commercially available radio receiver to a laptop computer and an antenna designed and built by Rockwell Collins, enabling them to receive WorldSpace signals from the AfriStar satellite during flight tests. WorldSpace broadcast their composite color graphical weather data files, which were multiplexed with normal audio streams, to the flat patch antenna mounted on a single-engine aircraft. The aircraft was equipped with a modified commercial S-DARS receiver, a Global Positioning Satellite (GPS) receiver, and a laptop computer with color display. Continuous data reception occurred during normal aircraft maneuvers performed throughout takeoff, cruise, and landing operations. In addition, engineers monitored receiver power levels during steep turns and banks. In most instances, the receiver was able to maintain acceptable power levels during all phases of flight and to obtain weather data with little or with the successful completion of ground and flight testing of a receiver and antenna in Johannesburg, South Africa, the team has started to prepare for experiments using highspeed aircraft in areas of the world with limited access to timely weather data. NASA plans to provide a more advanced antenna design and consultation support. This successful test of real-time aviation-related weather data is a positive step toward solving communications-specific issues associated with the dissemination of weather data directly to the cockpit.

Mallasch, Paul G.↗

NASA NTRS2015

ExMC Work Prioritization Process

Last year, NASA's Human Research Program (HRP) introduced the concept of a "Path to Risk Reduction" (PRR), which will provide a roadmap that shows how the work being done within each HRP element can be mapped to reducing or closing exploration risks. Efforts are currently underway within the Exploration Medical Capability (ExMC) Element to develop a structured, repeatable process for prioritizing work utilizing decision analysis techniques and risk estimation tools. The goal of this effort is to ensure that the work done within the element maximizes risk reduction for future exploration missions in a quantifiable way and better aligns with the intent and content of the Path to Risk Reduction. The Integrated Medical Model (IMM) will be used to identify those conditions that are major contributors of medical risk for a given design reference mission. For each of these conditions, potential prevention, screening, diagnosis, and treatment methods will be identified. ExMC will then aim to prioritize its potential investments in these mitigation methods based upon their potential for risk reduction and other factors such as vehicle performance impacts, near term schedule needs, duplication with external efforts, and cost. This presentation will describe the process developed to perform this prioritization and inform investment discussions in future element planning efforts. It will also provide an overview of the required input information, types of process participants, figures of merit, and the expected outputs of the process.

Simon, Matthew↗

DOE OSTI2020

After the hurricane: Validating a resilience assessment methodology

With increasing utility grid outages in the United States, there is growing interest in assessing risk and developing mitigation strategies to reduce the impact of grid outages. Working with the U.S. Air Force, the U.S. Department of Energy's National Renewable Energy Laboratory (NREL) developed a replicable energy resilience assessment methodology and investment decision tool to: (1) identify and score hazards and vulnerabilities at the site level; (2) analyze risks to energy infrastructure; and (3) identify and prioritize energy resilience investments. This work improves on existing resilience assessment methodologies and tools by combining a bottom-up, all-hazards assessment methodology with top-down geographic information system mapping capabilities to provide an innovative, dynamic tool for identifying and prioritizing actionable solutions. This process combines probabilistic forecasting with an iterative approach for continuously updating and reassessing risks to address temporal dynamism. Relationships among systems are modeled and visualized to estimate the effectiveness of resilience actions across multiple interdependent systems and inform financial priorities through cost-difficulty-impact trade-offs. The approach is validated in a case study at Tyndall Air Force Base (AFB) in Florida, which experienced a Category 5 hurricane in 2018. The risks and mitigation strategies identified pre-hurricane are compared with post-hurricane, realized impacts. The assessment effectively identifies risks and actions to increase site energy resilience, but the methodology can be enhanced though greater consideration of the interdependencies between the energy system and related systems like transportation, communication, and food/water systems, which impact the recovery of the energy system and the base.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

STOCHASTIC OPTIMIZATION FOR LONG TERM CAPITAL STRUCTURES, SYSTEMS, AND COMPONENTS REFURBISHMENT AND REPLACEMENT

As commercial nuclear power plants (NPPs) pursue extended plant operations in the form of Second License Renewals (SLRs), opportunities exist for these plants to provide capital investments to ensure long-term, safe, and economic performance. Several utilities have already announced their intention to pursue extended operations for one or more of their NPPs via SLR2. The goal of this research is to develop a riskinformed approach to evaluate and prioritize plant capital investments made in preparation for, and during the period of, extended plant operations to support decisions in NPP operations. In order to prioritize project selection via a riskinformed approach we developed a single decision-making tool that integrates safety/reliability, cost, and stochastic optimization models to provide users with data analysis capabilities to more cost effectively manage plant assets. Both stochastic analysis methods—such as Monte Carlo-based sampling strategies—and multi-stage stochastic optimization strategies are employed to provide priority lists to decisionmakers in support of risk-informed decisions. We applied the proposed method to a trial application of projected replacement/refurbishment expenditures for plant capital assets (i.e., Structures, Systems, and Components [SSCs]). The objective is to optimize the SSC replacement/refurbishment schedule in terms of economic constraints, data uncertainties, and SSC reliability data, as well to generate a priority list for maximizing returns on investment.

42 ENGINEERING↗

DOE OSTI2026

Long-Term Impacts of Constrained Transmission Deployment on the Cost-Reliability Tradeoff

Traditional Resource Adequacy (RA) frameworks in the U.S. undervalue the contributions of inter-regional transmission to resource adequacy during stress periods, focusing on the availability of nameplate capacity instead. However, availability of nameplate capacity does not always translate into electricity delivery, especially during tail events. Moreover, the rapid deployment of energy-limited resources and increasing electricity demand challenge existing resource adequacy frameworks and couple regional electricity demand and availability of supply via transmission. We propose a two-stage framework that goes beyond the existing capacity-centered approaches to reveal the RA contributions of transmission. In the first stage we introduce a multi-objective optimization framework to quantify the merits of transmission expansion via Pareto Frontiers under alternative futures of no transmission investment, primary energy resources availability and demand growth. The second stage focuses on tail events and leverages the results of the first stage to characterize the risk profile of regional consumers across the U.S. under the alternative energy futures. We find that no new transmission can lead to a more expensive and less reliable national grid across scenarios, however, the impact on regional RA can vary. The probabilistic analysis reveals that transmission investments can alleviate the tail risk of consumers, however, the availability of fuel resources does not always alleviate regional tail risks. Our findings inform policymakers and utilities on the prioritization of transmission investments to mitigate the risk of widespread outages, also for tail events, and ensure reliable and affordable electricity delivery to all.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Stochastic Analysis for Long Term Capital Structures, Systems, and Components Refurbishment and Replacement

As commercial Nuclear Power Plants (NPPs) pursue extended plant operation in the form of Second License Renewal (SLR), opportunities exist for these plants to provide capital investments to ensure long-term safe and economic performance. At the current time, several utilities have announced an intention to pursue extended operation for one or more of their NPPs via SLR . The goal of this research is to develop a risk-informed approach to evaluate and prioritize plant capital investments made in preparation for, and during the period of, extended plant operations to support decisions for NPP operations. Since the capital investments are influenced by various factors, such as markets, safety and regulatory, the decision-making process of NPP operations should take into account relevant factors for balancing risks, costs and profits. The traditional method of capital budgeting is based on the priority list of candidate projects using economic measures such as benefit-investment ratio, net present value (NPV) and internal rate of return. In the literatures, the problem of capital budgeting or the variant can be represented by an appropriate knapsack problem. The knapsack approach to capital budgeting takes as input as investment, along with the cost and profit of each project. The objective of capital budgeting is to find the combination of the binary decisions for every investment such that the overall profit is as large as possible. The output is a collection of projects to be carried out, and we refer this selected collection of projects as a project portfolio. One limitation of traditional optimization models for capital budgeting is that they do not account for risk/uncertainty in profit and cost streams associated with individual projects, they do not account for risk in resource availability in future years [1,2,3]. Projects can incur cost over-runs, especially when projects are large, performed infrequently, and when there is risk regarding technical viability, external contractors, and/or suppliers of requisite parts and materials. Occasionally, projects are performed ahead of schedule and with cost savings. Planned budgets for capital improvements can be cut and key personnel may be lost. Or, there may be surprise windfalls in budgets for maintenance activities due to decreased costs for “unplanned” maintenance. In these cases, how should we resolve capital budgeting when we have risk forecasts for costs, profits and budgets? One approach we proposed in this summary is to re-solve the optimization models based on assumed statistical distributions of given parameters. If these distributions were not available, a two-stage stochastic optimization approach can be used to provide priority lists to decision-makers to support better risk-informed decisions [4, 5]. In this summary, we will only focus on the first approach.

42 ENGINEERING↗

NASA NTRS2015

Technology Alignment and Portfolio Prioritization (TAPP): Advanced Methods in Strategic Analysis, Technology Forecasting and Long Term Planning for Human Exploration and Operations, Advanced Exploration Systems and Advanced Concepts

The Advanced Concepts Office (ACO) at NASA, Marshall Space Flight Center is expanding its current technology assessment methodologies. ACO is developing a framework called TAPP that uses a variety of methods, such as association mining and rule learning from data mining, structure development using a Technological Innovation System (TIS), and social network modeling to measure structural relationships. The role of ACO is to 1) produce a broad spectrum of ideas and alternatives for a variety of NASA's missions, 2) determine mission architecture feasibility and appropriateness to NASA's strategic plans, and 3) define a project in enough detail to establish an initial baseline capable of meeting mission objectives ACO's role supports the decision-making process associated with the maturation of concepts for traveling through, living in, and understanding space. ACO performs concept studies and technology assessments to determine the degree of alignment between mission objectives and new technologies. The first step in technology assessment is to identify the current technology maturity in terms of a technology readiness level (TRL). The second step is to determine the difficulty associated with advancing a technology from one state to the next state. NASA has used TRLs since 1970 and ACO formalized them in 1995. The DoD, ESA, Oil & Gas, and DoE have adopted TRLs as a means to assess technology maturity. However, "with the emergence of more complex systems and system of systems, it has been increasingly recognized that TRL assessments have limitations, especially when considering [the] integration of complex systems." When performing the second step in a technology assessment, NASA requires that an Advancement Degree of Difficulty (AD2) method be utilized. NASA has used and developed or used a variety of methods to perform this step: Expert Opinion or Delphi Approach, Value Engineering or Value Stream, Analytical Hierarchy Process (AHP), Technique for the Order of Prioritization by Similarity to Ideal Solution (TOPSIS), and other multi‐criteria decision-making methods. These methods can be labor-intensive, often contain cognitive or parochial bias, and do not consider the competing prioritization between mission architectures. Strategic Decision-Making (SDM) processes cannot be properly understood unless the context of the technology is understood. This makes assessing technological change particularly challenging due to the relationships "between incumbent technology and the incumbent (innovation) system in relation to the emerging technology and the emerging innovation system." The central idea in technology dynamics is to consider all activities that contribute to the development, diffusion, and use of innovations as system functions. Bergek defines system functions within a TIS to address what is actually happening and has a direct influence on the ultimate performance of the system and technology development. ACO uses similar metrics and is expanding these metrics to account for the structure and context of the technology. At NASA technology and strategy is strongly interrelated. NASA's Strategic Space Technology Investment Plan (SSTIP) prioritizes those technologies essential to the pursuit of NASA's missions and national interests. The SSTIP is strongly coupled with NASA's Technology Roadmaps to provide investment guidance during the next four years, within a twenty-year horizon. This paper discusses the methods ACO is currently developing to better perform technology assessments while taking into consideration Strategic Alignment, Technology Forecasting, and Long Term Planning.

Funaro, Gregory V.↗

NASA NTRSDate not supplied

NASA's Small Spacecraft and Distributed Systems: Development and Demonstration of Technologies Enabling Swarms and New Spacecraft Platforms with AI and Edge Computing

NASA’s Small Spacecraft & Distributed Systems (SSDS) within the Research and Technology Mission Directorate (RTMD) expands U.S. capability to execute unique missions through targeted investment, rapid development, and flight demonstration of small spacecraft technologies applicable to exploration, science and the commercial space sector. SSDS strategically invests in technology development and on-orbit demonstrations executed across NASA, other government agencies, industry, and academia. The program’s University SmallSat Technology Partnerships initiative awards academic researchers with the opportunity to collaborate with NASA to mature innovative technology. Capabilities aligned with RTMD’s technology shortfalls and interests - power, processing, propulsion, sensors, communications, autonomous navigation, architectures, and advanced applications like artificial intelligence (AI), machine learning, and edge computing - are prioritized in SSDS investments. These investments enable distributed, autonomous, and cooperative small spacecraft systems that support swarm missions extending beyond low Earth orbit into cislunar and deep space. This paper highlights representative SSDS flight demonstrations that mature these capabilities to enable a future operational infrastructure needed to support sustained exploration of the Moon and beyond. SSDS’s investment strategy emphasizes rapid development and on-orbit demonstration to validate spacecraft technologies required for swarms and distributed mission architectures. The Starling swarm technology demonstration mission exemplifies this approach by advancing distributed spacecraft autonomy, cooperative operations, and space situational awareness. Extended flight testing and ongoing studies of next generation swarm configurations and on-orbit space traffic monitoring and management continue to inform future swarm designs. DiskSat’s four-spacecraft demonstration mission represents SSDS’s strategic vision to expand the design space for future small spacecraft through its commitment to advance novel platform concepts that can impact how science is performed on orbit. Continuing to invest in future platforms, the notional PY12 concept is a 12-spacecraft swarm hosting neuromorphic processors and is envisioned as an on-orbit testbed for AI, edge computing, and positioning, navigation and timing technologies. SSDS also invests in single-spacecraft technology demonstrations that underpin the success of future swarm missions and accelerate the availability of validated technologies across the small spacecraft ecosystem. Examples of such demonstrations include Pathfinder Technology Demonstrator-3 (PTD-3), which performed high-rate optical communications; PTD-R, which demonstrated a camera capable of simultaneous ultraviolet and short-wave infrared optical sensing; and CAPSTONE, the Cislunar Autonomous Positioning System Technology and Operations Navigation Experiment, which validated autonomous navigation in cislunar space. Collectively, SSDS-funded demonstrations advance capabilities across swarms and illustrate a coordinated investment strategy to mature high-impact technologies required for autonomous, distributed, and cooperative small spacecraft systems for low Earth orbit, cislunar, and deep space applications. Technology demonstrations strengthen SSDS partnerships with industry, academia, and other government agencies, and promote small spacecraft community adoption of capabilities required to close technical gaps for swarm missions.

Jan Stupl↗

NASA NTRSDate not supplied

NASA's Small Spacecraft and Distributed Systems: Development and Demonstration of Technologies Enabling Swarms and New Spacecraft Platforms with AI and Edge Computing

Jan Stupl↗

DOE OSTI2020

Scalable and Actionable Performance Measures for Traffic Signal Systems using Probe Vehicle Trajectory Data

Scalable and actionable performance measures for traffic signal systems provide opportunities for practitioners to measure and improve the transportation network. Historically, traffic signal improvements have relied on scheduled signal retiming based on limited data collection, or on the public to call and alert engineers of an issue. This inefficient method of improving signal timing led to the creation of automated traffic signal performance measures (ATSPMs). These metrics rely on expensive infrastructure, including detection and communications, which has produced barriers for numerous agencies to fully adopt. Recently, third-party data providers have begun to release vehicle trajectory data, which allows for enhanced signal metrics with no investment in physical equipment. The purpose of this study is to demonstrate the use of these data and summarize the scalability of the created metrics. This work builds on previous efforts to quantify signal performance on nine intersections in Michigan, U.S. Ten signalized corridors in Columbus, Ohio, were chosen to scale a performance assessment using crowdsourced trajectory data. A total of 136 intersections were assessed in 2-h intervals using data from all weekdays in 2017. High-level corridor summary metrics including average percent of vehicles stopping (18%–32%), average delay (9.4–20.5 s), and level of travel time reliability (1.23–2.73) were calculated for each corridor direction. Intersection-level metrics were also introduced, which can be used by practitioners to identify problems, improve signal timings, and prioritize future infrastructure investments.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2021

Ride-hailing and taxi versus walking: Long term forecasts and implications from large-scale behavioral data

Introduction: Although ride-hailing and taxi trips can potentially reduce single-occupant vehicle trips and auto ownership, they can also replace pedestrian trips. Because physical activity is associated with improved health outcomes, the extent to which ride-hailing and taxi travel captures walking's mode share is of interest to policymakers. Methods: Based on large-scale behavioral data from the 2017 U.S. National Household Travel Survey, this paper reports on the development of a full Bayesian logistic regression model for determining the mode split between (1) ride-hailing and taxi and (2) walk while accounting for unobserved heterogeneity. The results from the stand-alone model inform two longer-term travel forecasting scenarios: a) higher risk of walk trips converting to ride-hailing and taxi, specifically in the future with high prevalence of automated vehicles, b) higher probability of such trips remaining as walking. Results: The results revealed that some of the important characteristics that increase the likelihood of a traveler using the ride-hailing and taxi mode versus walking include having a longer trip, using a smartphone to access the internet, having an interest in technologies, having a medical condition, and living in a metropolitan area with rail access. Further, the results from the first scenario suggest that an overall increase of up to 2.9% in the ride-hailing and taxi mode share may be expected. The second scenario shows that between 68% and 76% of ride-hailing and taxi trips could be diverted to walking if supportive pedestrian infrastructure were provided in the case study locations. The planning process can be adapted to consider not only congestion, crash, and emissions impacts of such shifts but also the effects of a loss of physical activity. Conclusions: The study findings show how the ride-hailing and taxi mode competes with walking. Further, the findings enable planners to update their regional travel forecasting models; policy makers can thus encourage active travel by prioritizing pedestrian infrastructure investments that may divert ride-hailing and taxi trips to walking. However, equity should be a key consideration to ensure that addressing the competition between these two modal choices does not hinder the provision of pedestrian facilities in communities that depend on walking.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2020

An iterative learning and inference approach to managing dynamic cyber-vulnerabilities of complex systems

As modern systems become increasingly reliant on cyber-technologies and continue to be integrated with physical systems, managing risks from deliberate and non-deliberate sources is a significant research challenge. Unlike strictly physical systems, cyber-enabled physical systems are influenced by dynamic and evolving technologies, environments, and attack mechanisms. As a result, vulnerabilities are rapidly changing and difficult to detect and manage. While there is recent interest in the dynamic properties of performance through resilience analysis, limited research addresses the dynamic nature of cyber-system vulnerability. This paper presents a dynamic iterative learning approach to evaluate the state of health for systems as related to cyber-vulnerabilities. These time-varying system health characteristics may not be visible, but can be inferred using observable characteristics. The approach recognizes that multiple types of vulnerabilities need to be included in a holistic system health assessment. The methods are applied to the Common Vulnerability Scoring System database containing over 100,000 documented cybersecurity vulnerabilities. This work is the first to acknowledge the dynamic properties of cyber-vulnerability, while also inferring system health using observable data and hidden states of system health. This work will be of interest to managers of large-scale cyber-enabled physical systems who are seeking to prioritize system health investments.

Chatterjee, Samrat↗

DOE OSTI2021

Enlightened Education: Solar Engineering Design to Energize School Facilities

Here, this paper explores the potential for universities, colleges, and K-12 schools to implement solar electric infrastructure projects on their campuses that not only provide financial savings but also provide learning environments and instructional opportunities for students. A recent case study at Madison College is presented for a 1.85 MW photovoltaic system that is the largest solar rooftop installation in the State of Wisconsin. The system was designed with several unique features to facilitate public access, provide students with hands-on interaction, and compare and contrast several different types of solar equipment. Special engineering design considerations should be made when installing solar on schools, and recommended practices from the Madison College experience are detailed. Madison College completed a Solar Roadmap in order to prioritize and sequence investment in solar across the multiple buildings and campus locations operated by the college. The featured installation was the first project within that plan. A ten-step guide on how to create a solar roadmap is shared, so that other schools can learn from Madison College’s experience and replicate the process for their own institutions.

14 SOLAR ENERGY↗