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At least 1,207 records · Page 67

Constellation Ground Systems Launch Availability Analysis: Enhancing Highly Reliable Launch Systems Design

Success of the Constellation Program's lunar architecture requires successfully launching two vehicles, Ares I/Orion and Ares V/Altair, in a very limited time period. The reliability and maintainability of flight vehicles and ground systems must deliver a high probability of successfully launching the second vehicle in order to avoid wasting the on-orbit asset launched by the first vehicle. The Ground Operations Project determined which ground subsystems had the potential to affect the probability of the second launch and allocated quantitative availability requirements to these subsystems. The Ground Operations Project also developed a methodology to estimate subsystem reliability, availability and maintainability to ensure that ground subsystems complied with allocated launch availability and maintainability requirements. The verification analysis developed quantitative estimates of subsystem availability based on design documentation; testing results, and other information. Where appropriate, actual performance history was used for legacy subsystems or comparative components that will support Constellation. The results of the verification analysis will be used to verify compliance with requirements and to highlight design or performance shortcomings for further decision-making. This case study will discuss the subsystem requirements allocation process, describe the ground systems methodology for completing quantitative reliability, availability and maintainability analysis, and present findings and observation based on analysis leading to the Ground Systems Preliminary Design Review milestone.

Gernand, Jeffrey L.↗

Propulsion Technology Lifecycle Operational Analysis

The paper presents the results of a focused effort performed by the members of the Space Propulsion Synergy Team (SPST) Functional Requirements Sub-team to develop propulsion data to support Advanced Technology Lifecycle Analysis System (ATLAS). This is a spreadsheet application to analyze the impact of technology decisions at a system-of-systems level. Results are summarized in an Excel workbook we call the Technology Tool Box (TTB). The TTB provides data for technology performance, operations, and programmatic parameters in the form of a library of technical information to support analysis tools and/or models. The lifecycle of technologies can be analyzed from this data and particularly useful for system operations involving long running missions. The propulsion technologies in this paper are listed against Chemical Rocket Engines in a Work Breakdown Structure (WBS) format. The overall effort involved establishing four elements: (1) A general purpose Functional System Breakdown Structure (FSBS). (2) Operational Requirements for Rocket Engines. (3) Technology Metric Values associated with Operating Systems (4) Work Breakdown Structure (WBS) of Chemical Rocket Engines The list of Chemical Rocket Engines identified in the WBS is by no means complete. It is planned to update the TTB with a more complete list of available Chemical Rocket Engines for United States (US) engines and add the Foreign rocket engines to the WBS which are available to NASA and the Aerospace Industry. The Operational Technology Metric Values were derived by the SPST Sub-team in the form of the TTB and establishes a database for users to help evaluate and establish the technology level of each Chemical Rocket Engine in the database. The Technology Metric Values will serve as a guide to help determine which rocket engine to invest technology money in for future development.

Robinson, John W.↗

Decision paths in complex tasks

Complex real world action and its prediction and control has escaped analysis by the classical methods of psychological research. The reason is that psychologists have no procedures to parse complex tasks into their constituents. Where such a division can be made, based say on expert judgment, there is no natural scale to measure the positive or negative values of the components. Even if we could assign numbers to task parts, we lack rules i.e., a theory, to combine them into a total task representation. We compare here two plausible theories for the amalgamation of the value of task components. Both of these theories require a numerical representation of motivation, for motivation is the primary variable that guides choice and action in well-learned tasks. We address this problem of motivational quantification and performance prediction by developing psychophysical scales of the desireability or aversiveness of task components based on utility scaling methods (Galanter 1990). We modify methods used originally to scale sensory magnitudes (Stevens and Galanter 1957), and that have been applied recently to the measure of task 'workload' by Gopher and Braune (1984). Our modification uses utility comparison scaling techniques which avoid the unnecessary assumptions made by Gopher and Braune. Formula for the utility of complex tasks based on the theoretical models are used to predict decision and choice of alternate paths to the same goal.

Galanter, Eugene↗

Decision Support Tool for Risk Assessment & Maneuver Planning in Collision Avoidance

As the quantity of orbital debris continues to grow, so too does the rate of conjunction messages that suggest possible collisions between high value payloads and debris. The abundance of these conjunction messages, and eventual misses, has led to a culture of ignored alerts, and an increase in satellite operation costs as a result of the frequent need to plan resources for maneuver planning and execution. The loss of “trust” in conjunction alerts is due to the poorly characterized evolution in probability of collision (Pc) as time approaches the time of closest approach (TCA) between two objects, as well as the interpretation of Pc in the context of maneuver planning. To address these problems, and in collaboration with the NASA Conjunction Assessment Risk Analysis (CARA) program, the Industrial Sciences Group has developed a novel Maneuver Decision Support System (MDSS) to assist satellite operations in conjunction assessment and Maneuver planning. It provides a meaningful and intuitive Urgency metric for actionable maneuver decisions, based on the physical dynamics of conjunctions. It is based on a forecast of the evolution of Pc over time and represents an advance over current methods that are in use for satellite conjunction monitoring and planning. The result is to give satellite operators a validated decision support systems to plan for maneuver execution or mitigation or monitoring up to 3 days before TCA.

Decision Support Tool↗

Incremental development and prototyping in current laboratory software development projects: Preliminary analysis

Several Laboratory software development projects that followed nonstandard development processes, which were hybrids of incremental development and prototyping, are being studied. Factors in the project environment leading to the decision to use a nonstandard development process and affecting its success are analyzed. A simple characterization of project environment based on this analysis is proposed, together with software development approaches which have been found effective for each category. These approaches include both documentation and review requirements.

Griesel, Martha Ann↗

The Challenger disaster was caused by an Apollo decision

NASA’s view of risk changed between early Apollo and the Space Shuttle. Risk was a known serious problem at the beginning of Apollo and the risk estimates were disturbingly high. To avoid public concern, risk analysis was discontinued. Risk analysis was avoided in Shuttle, leading to an unnecessarily risky design. The immediate cause of the Challenger tragedy was the mistaken decision to launch in cold weather. The fundamental cause was the high risk of the Shuttle design. Before Challenger, management thought and testified that the probability of an accident was 1 in 100,000. After Challenger, Probabilistic Risk Analysis (PRA) found a roughly 1 in 100 chance of a Shuttle failure. The recent Orion design uses the safer Apollo approach, with a hardened capsule, launch abort escape, and the crew placed above the rocket tanks and engines. During Apollo it was estimated that, “assuming all elements from propulsion to rendezvous and life support were done as well or better than ever before, that 30 astronauts would be lost before 3 were returned safely to the Earth.” The chance of astronaut survival was only 10%. After the Apollo 1 tragedy, the awareness of risk led to an intense focus on achieving safety. “The only possible explanation for the astonishing success – no losses in space and on time – was that every participant at every level in every area far exceeded the norm of human capabilities.” During Apollo, a NASA PRA found that the chance of success was “less than 5 percent.” The NASA Administrator felt that “the numbers could do irreparable harm,” and discontinued numerical risk assessment.

Harry W Jones↗

Performance Assessment of Pump-and-Treat Systems

Pump-and-treat (P&T) is a widely applied remedy for groundwater remediation at many types of sites for multiple types of contaminants. Decisions regarding major changes in the remediation approach are an important element of environmental remediation management for a site using P&T. While existing guidance documents provide information on design, operation, and optimization for P&T systems, these documents do not provide specific technical guidance to support remedy decisions regarding when to transition to a new remedy or to initiate closure of the P&T remedy. A structured approach for P&T performance assessment was developed and is described herein, using analysis of three example P&T systems. These examples highlight key aspects of the performance assessment decision logic and represent assessment outcomes associated with optimizing the P&T system, transitioning from P&T to natural attenuation, and supplementing P&T with another technology to hasten transition to natural attenuation.

54 ENVIRONMENTAL SCIENCES↗

Non-negative Tensor Factorization for Robust Exploratory Big-Data Analytics

Currently, large multidimensional datasets are being accumulated in almost every field. Data are: (1) collected by distributed sensor networks in real-time all over the globe, (2) produced by large-scale experimental measurements or engineering activities, (3) generated by high-performance simulations, and (4) gathered by electronic communications and socialnetwork activities, etc. Simultaneous analysis of these ultra-large heterogeneous multidimensional datasets is often critical for scientific discoveries, decision-making, emergency response, and national and global security. The importance of such analyses mandates the development of the next-generation of robust machine learning (ML) methods and tools for bigdata exploratory analysis.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Integrated Software for Analyzing Designs of Launch Vehicles

Launch Vehicle Analysis Tool (LVA) is a computer program for preliminary design structural analysis of launch vehicles. Before LVA was developed, in order to analyze the structure of a launch vehicle, it was necessary to estimate its weight, feed this estimate into a program to obtain pre-launch and flight loads, then feed these loads into structural and thermal analysis programs to obtain a second weight estimate. If the first and second weight estimates differed, it was necessary to reiterate these analyses until the solution converged. This process generally took six to twelve person-months of effort. LVA incorporates text to structural layout converter, configuration drawing, mass properties generation, pre-launch and flight loads analysis, loads output plotting, direct solution structural analysis, and thermal analysis subprograms. These subprograms are integrated in LVA so that solutions can be iterated automatically. LVA incorporates expert-system software that makes fundamental design decisions without intervention by the user. It also includes unique algorithms based on extensive research. The total integration of analysis modules drastically reduces the need for interaction with the user. A typical solution can be obtained in 30 to 60 minutes. Subsequent runs can be done in less than two minutes.

Philips, Alan D.↗

Revisit of Energy Use and Technologies of High Performance Buildings

Energy consumed by buildings accounts for one third of the world?s total primary energy use. Associated with the conscious of energy savings in buildings, High Performance Buildings (HPBs) has surged across the world, with wide promotion and adoption of various performance rating and certification systems. It is valuable to look into the actual energy performance of HPBs and to understand their influencing factors. To shed some light on this topic, this paper conducted a series of portfolio analysis based on a database of 51 high performance office buildings across the world. Analyses showed that the actual site Energy Use Intensity (EUI) of the 51 buildings varied by a factor of up to 11, indicating a large scale of variation of the actual energy performance of the current HPBs. Further analysis of the correlation between EUI and climate elucidated ubiquitous phenomenon of EUI scatter throughout all climate zones, implying that the weather is not a decisive factor, although important, for the actual energy consumption of an individual building. On the building size via EUI, analysis disclosed that smaller buildings have a tendency to achieving lower energy use. Even so, the correlation is not absolute since some large buildings demonstrated low energy use while some small buildings performed opposite. Concerning the technologies, statistics indicated that the application of some technologies had correlations with some specific building size and climate characteristic. However, it was still hard to pinpoint a set of technologies which was directly correlative with a group of low EUI buildings. It is concluded that no a single factor essentially determines the actual energy performance of HPBs. To deliver energy-efficient buildings, an integrated design taking account of climate, technology, occupant behavior as well as operation and maintenance should be implemented.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Reliability-Informed Life Cycle Warranty Cost and Life Cycle Analysis of Newly Manufactured and Remanufactured Units

Standard life cycle techniques such as life cycle warranty cost (LCWC) analysis and life cycle analysis (LCA) are used to respectively quantify the relative economical and environmental advantages of remanufactured goods while simultaneously identifying avenues for improvement. In this paper, we contribute to the literature on life cycle studies by incorporating reliability into LCWC analysis and LCA with the goal of improving long-term/multiple life cycle decision making. We develop a branched power-law model to incorporate the physical degradation mechanisms leading to reduced reuse rates of system parts over multiple life cycles. We then follow a standard LCA protocol to quantify the difference between a new unit and its remanufactured version in terms of environmental impact items such as abiotic depletion potential, global warming potential, and energy consumption. We then devise four practical warranty policies that vary in the choice of replacement and/or provision for extended warranty. All possible replacement scenarios for multiple life cycles are explored for each policy and a mathematically rigorous framework is provided, where the reliability information is used to calculate probabilistic LCWC and life cycle impact items. This reliability-informed LCWC analysis and LCA framework enables design engineers to compare design options and warranty policies by quantifying both economical and environmental impacts to aid in decision making. Although the framework is presented in a general form applicable to any engineered system, we demonstrate the utility of this framework by using a case study of an infinitely variable transmission used in agricultural equipment.

42 ENGINEERING↗

Automated Extraction of Energy Systems Information from Remotely Sensed Data: A Review and Analysis

We report high quality energy systems information is a crucial input to energy systems research, modeling, and decision-making. Unfortunately, actionable information about energy systems is often of limited availability, incomplete, or only accessible for a substantial fee or through a non-disclosure agreement. Recently, remotely sensed data (e.g., satellite imagery, aerial photography) have emerged as a potentially rich source of energy systems information. However, the use of these data is frequently challenged by its sheer volume and complexity, precluding manual analysis. Recent breakthroughs in machine learning have enabled automated and rapid extraction of useful information from remotely sensed data, facilitating large-scale acquisition of critical energy system variables. Here we present a systematic review of the literature on this emerging topic, providing an in-depth survey and review of papers published within the past two decades. We first taxonomize the existing literature into ten major areas, spanning the energy value chain. Within each research area, we distill and critically discuss major features that are relevant to energy researchers, including, for example, key challenges regarding the accessibility and reliability of the methods. We then synthesize our findings to identify limitations and trends in the literature as a whole, and discuss opportunities for innovation. These include the opportunity to extend the methods beyond electricity to broader energy systems and wider geographic areas; and the ability to expand the use of these methods in research and decision making as satellite data become cheaper and easier to access. We also find that there are persistent challenges: limited standardization and rigor of performance assessments; limited sharing of code, which would improve replicability; and a limited consideration of the ethics and privacy of data.

97 MATHEMATICS AND COMPUTING↗

Research Needs and New Capabilities for Retail Electricity Rate Analysis

Retail electricity rates are at the center of supply- and demand-side changes in future power systems and influence system costs and DER adoption decisions, all with important implications for system reliability, resiliency, and energy affordability. Building on decades of research experience and analytical insights at Lawrence Berkeley National Laboratory (LBNL) and the National Renewable Energy Laboratory (NREL), the report identifies key near-term analysis questions, enhancements to existing capabilities, and longer-term new capabilities to provide actionable insights for electricity system decision-makers, including state utility regulators, electric and gas utilities, ratepayer advocates, and DER solution providers.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A Pathway for the Development of Advanced Reactor Mechanistic Source Term Modeling and Simulation Capabilities

Source term analysis, or the estimation of the potential radionuclide release to the environment during reactor events, is a central focus of the reactor licensing process and a vital part of risk-informed reactor design approaches. A mechanistic source term (MST) analysis is designed to realistically model the release and transport of radionuclides from the source to the environment for specific scenarios, while accounting for retention or transmutation phenomena and associated uncertainties. The objective of MST analyses, in comparison to bounding or conservative source term assessments, is to provide a non-biased representation of reactor risk and improve the information available for siting, emergency planning, and reactor design decisions. In support of the advanced reactor community in its pursuit of MST analysis capabilities, this work outlines a recommended research pathway for the development of MST modeling and simulation (mod/sim) tools.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Linear systematics mitigation in galaxy clustering in the Dark Energy Survey Year 1 Data

ABSTRACT We implement a linear model for mitigating the effect of observing conditions and other sources of contamination in galaxy clustering analyses. Our treatment improves upon the fiducial systematics treatment of the Dark Energy Survey (DES) Year 1 (Y1) cosmology analysis in four crucial ways. Specifically, our treatment (1) does not require decisions as to which observable systematics are significant and which are not, allowing for the possibility of multiple maps adding coherently to give rise to significant bias even if no single map leads to a significant bias by itself, (2) characterizes both the statistical and systematic uncertainty in our mitigation procedure, allowing us to propagate said uncertainties into the reported cosmological constraints, (3) explicitly exploits the full spatial structure of the galaxy density field to differentiate between cosmology-sourced and systematics-sourced fluctuations within the galaxy density field, and (4) is fully automated, and can therefore be trivially applied to any data set. The updated correlation function for the DES Y1 redMaGiC catalogue minimally impacts the cosmological posteriors from that analysis. Encouragingly, our analysis does improve the goodness-of-fit statistic of the DES Y1 3 × 2pt data set (Δχ2 = −6.5 with no additional parameters). This improvement is due in nearly equal parts to both the change in the correlation function and the added statistical and systematic uncertainties associated with our method. We expect the difference in mitigation techniques to become more important in future work as the size of cosmological data sets grows.

79 ASTRONOMY AND ASTROPHYSICS↗

A Data-Driven Approach to Recognizing and Understanding Human Contributions to Aviation Safety

Data-driven decisions about safety management and design of safety-critical systems are limited by the available data, which influence, and are influenced by, how decision makers characterize problems and identify solutions. In the commercial aviation domain, large volumes of data are collected and analyzed on the failures and errors that result in infrequent incidents and accidents, but in the absence of data on safety-producing behaviors, safety management and system design decisions are based on a small sample of non-representative safety data. Analysis of aviation accident data suggests that human error is implicated in up to 80% of accidents, which has been used to justify future visions for aviation in which the roles of human operators are greatly diminished or eliminated in the interest of creating a safer aviation system. However, failure to fully consider the human contributions to aviation safety represents a significant and largely unrecognized risk when making policy decisions about safety management and system design. Opportunities exist to leverage the vast amount of data that have already been collected, or could be easily obtained, to increase our understanding of human contributions to safety in commercial aviation. This presentation will focus on those opportunities as well as the challenges associated with collecting and analyzing data on operators’ safety-producing behaviors.

Safety↗

Component Importance and Interdependence Analysis for Transmission, Distribution and Communication Systems

For critical infrastructure restoration planning, the real-time scheduling and coordination of system restoration efforts, the key in decision-making is to prioritize those critical components that are out of service during the restoration. For this purpose, there is a need for component importance analysis. While it has been investigated extensively for individual systems, component importance considering interdependence among transmission, distribution and communication (T&D&C) systems has not been systematically analyzed and widely adopted. In this study, we propose a component importance assessment method in the context of interdependence between T&D&C networks. Analytic methods for multilayer networks and a set of metrics have been applied for assessing the component importance and interdependence between T&D&C networks based on their physical characteristics. The proposed methodology is further validated with integrated synthetic Illinois regional transmission, distribution, and communication (T&D&C) systems, the results reveal the unique characteristics of component/node importance, which are strongly affected by the network topologies and cross-domain node mapping.

24 POWER TRANSMISSION AND DISTRIBUTION↗

System analysis in rotorcraft design: The past decade

Rapid advances in the technology of electronic digital computers and the need for an integrated synthesis approach in developing future rotorcraft programs has led to increased emphasis on system analysis techniques in rotorcraft design. The task in systems analysis is to deal with complex, interdependent, and conflicting requirements in a structured manner so rational and objective decisions can be made. Whether the results are wisdom or rubbish depends upon the validity and sometimes more importantly, the consistency of the inputs, the correctness of the analysis, and a sensible choice of measures of effectiveness to draw conclusions. In rotorcraft design this means combining design requirements, technology assessment, sensitivity analysis and reviews techniques currently in use by NASA and Army organizations in developing research programs and vehicle specifications for rotorcraft. These procedures span simple graphical approaches to comprehensive analysis on large mainframe computers. Examples of recent applications to military and civil missions are highlighted.

Galloway, Thomas L.↗