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The presentation was intended for the Accord Technical Exchange Meeting (ATEM), September 3, 2020. Multiple lines of evidence were evaluated in the Use Attainability Analysis for Upper Sandia Canyon.
In technical report writing, two needs which must be met if reports are to be useable by an audience are the language needs and the technical needs of that particular audience. A heuristic analysis helps to decide the most suitable format for information; that is, whether the information should be presented verbally or visually. The report writing process should be seen as an organic whole which can be divided and subdivided according to the writer's purpose, but which always functions as a totality. The tagmemic heuristic, because it itself follows a process of deconstructing and reconstructing information, lends itself to being a useful approach to the teaching of technical writing. By applying the abstract questions this heuristic asks to specific parts of the report. The language and technical needs of the audience are analyzed by examining the viability of the solution within the givens of the corporate structure, and by deciding which graphic or verbal format will best suit the writer's purpose. By following such a method, answers which are both specific and thorough in their range of application are found.
An assessment of state-of-the-art technologies that are applicable to silicon solar cell and solar cell module fabrication is provided. The assessment consists of a technical feasibility evaluation and a cost projection for high-volume production of silicon solar cell modules. The cost projection was approached from two directions; a design-to-cost analysis assigned cost goals to each major process element in the fabrication scheme, and a cost analysis built up projected costs for alternate technologies for each process element. A technical evaluation was used in combination with the cost analysis to identify a baseline low cost process. A novel approach to metal pattern design based on minimum power loss was developed. These design equations were used as a tool in the evaluation of metallization technologies.
Software Quality Assurance (SQA) is an important component of the software development process. SQA processes provide assurance that the software products and processes in the project life cycle conform to their specified requirements by planning, enacting, and performing a set of activities to provide adequate confidence that quality is being built into the software. Typical techniques include: (1) Testing (2) Simulation (3) Model checking (4) Symbolic execution (5) Management reviews (6) Technical reviews (7) Inspections (8) Walk-throughs (9) Audits (10) Analysis (complexity analysis, control flow analysis, algorithmic analysis) (11) Formal method Our work over the last few years has resulted in substantial knowledge about SQA techniques, especially the areas of technical reviews and inspections. But can we apply the same QA techniques to the system development process? If yes, what kind of tailoring do we need before applying them in the system engineering context? If not, what types of QA techniques are actually used at system level? And, is there any room for improvement.) After a brief examination of the system engineering literature (especially focused on NASA and DoD guidance) we found that: (1) System and software development process interact with each other at different phases through development life cycle (2) Reviews are emphasized in both system and software development. (Figl.3). For some reviews (e.g. SRR, PDR, CDR), there are both system versions and software versions. (3) Analysis techniques are emphasized (e.g. Fault Tree Analysis, Preliminary Hazard Analysis) and some details are given about how to apply them. (4) Reviews are expected to use the outputs of the analysis techniques. In other words, these particular analyses are usually conducted in preparation for (before) reviews. The goal of our work is to explore the interaction between the Quality Assurance (QA) techniques at the system level and the software level.
SAF provides a promising approach to aid the rising jet fuel demand from increased travel around the world and reduce the lifecycle emissions from the aviation sector. Although the feasibility of SAF pathways has been demonstrated through economic and environmental metrics quantification, the models used to quantify these variables have a high degree of variability in terms of accuracy and thereby reliability. To understand how to adopt and commercialize SAF, we need to harmonize these process models and assess metrics and technical limitations related to their production technologies. We find the production cost of SAF using hydro processed fatty acids and esters (HEFA), Fischer-Tropsch (FT), and alcohol-to-jet (ATJ) to be $\$$3-$\$$6/gallon gasoline equivalent (gge) and life cycle emissions to be lower than Jet A, except for ATJ using corn grain (≤25%). HEFA utilizing oil feedstocks has the lowest production cost (~$\$$2.9/gge) and highest jet yield (>150 gge/dry ton), while FT has the largest emission reduction (94%) compared to fossil jet. A unique contribution of this study is a comparative analysis of metrics related to SAF processes across technical, economic, and sustainability aspects. A cross-comparison of these metrics shows HEFA using fats, oils, and grease have the most favorable ratings, while HEFA using algae and ATJ using corn stover have more neutral and unfavorable ratings, respectively. These ratings can be improved by implementing the right combination of practical and technological advancements.
This is a listing of recent unclassified RTO technical publications processed by the NASA Center for AeroSpace Information from January 1, 2001 through March 31, 2001 available on the NASA Aeronautics and Space Database. Contents include 1) Cognitive Task Analysis; 2) RTO Educational Notes; 3) The Capability of Virtual Reality to Meet Military Requirements; 4) Aging Engines, Avionics, Subsystems and Helicopters; 5) RTO Meeting Proceedings; 6) RTO Technical Reports; 7) Low Grazing Angle Clutter...; 8) Verification and Validation Data for Computational Unsteady Aerodynamics; 9) Space Observation Technology; 10) The Human Factor in System Reliability...; 11) Flight Control Design...; 12) Commercial Off-the-Shelf Products in Defense Applications.
Argonne National Laboratory and Idaho National Laboratory, through a Department of Energy Gateway for Accelerated Innovation in Nuclear Voucher, supported key analysis needs of Radiant related to (i) air jacket thermal fluid performance, (ii) evaluation of decay heat source terms defining air jacket technical requirements, and (iii) assessment of modeling methodologies employed for core analysis. All of these activities center on numerical simulation of various aspects of Kaleidos using the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, the Cardinal multiphysics application, the OpenMC Monte Carlo code, and the Nek5000 computational fluid dynamics (CFD) code. This project builds upon an earlier Nuclear Energy Advanced Modeling and Simulation (NEAMS) Thermal-Hydraulic (T/H) Center of Excellence (CoE) project focused on initial demonstration of Cardinal multiphysics simulation of High Temperature Gas Reactors (HTGRs) and now focuses on Radiant’s Kaleidos concept.
The activities described in this (report) are related to the analysis and testing of graphite and mine tailing samples provided by the Recipient for the extraction and recovery of embedded metals. This report focused on recovery of platinum group metals (PGMs), which appear in relatively high abundance, particularly technically important elements ruthenium and rhodium. Work performed involved assessment of materials followed by extraction tests using two methods. A novel electrochemically-driven route was compared to a chemical route for extraction of the metals. The electrochemically driven route showed similar results while producing the lixiviant in the electrochemical cell, hence reducing chemical requirements.
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Life-Cycle Cost Analysis Framework for Water Efficiency Measures: Guidance Designed for Federal Agencies (hereafter referred to as “this report”) provides a technical framework for federal agencies to conduct a life-cycle cost analysis (LCCA) for water efficiency projects in accordance with 42 U.S.C. § 8253. This report leverages insights from the 2023 report, PNNL-34006, Water and Wastewater Annual Price Escalation Rates for Selected Cities Across the United States: 2023 Edition (Unger et al. 2023). The primary objective of this report is to provide a framework to assist federal agencies with evaluating the full economic impact of water efficiency projects by assessing both initial investments and long-term operational benefits. An LCCA can provide a comprehensive view of all costs associated with a water efficiency project, including initial investment, ongoing operations and maintenance (O&M), and eventual disposal or replacement, ensuring the most cost-effective solution is selected. The LCCA methodology outlined in this report enables users to compare base case scenarios with potential alternatives using a standardized present value approach. It incorporates key cost components such as energy, water and wastewater, installation, O&M, and equipment replacement. Additionally, the framework introduces relevant evaluation metrics, such as the net savings and the savings-to-investment ratio, to ensure that water efficiency measures are economically justified over the lifespan of the project. To support practical application, this report also describes various water efficiency strategies that may be analyzed using an LCCA, including plumbing retrofits, irrigation upgrades, alternative water use, and cooling system improvements. By applying this framework, federal agencies can ensure compliance with regulatory mandates while maximizing the return on investment and contributing to resilient water management practices. The information provided in this report is aligned with the Federal Energy Management Program (FEMP) life-cycle cost (LCC) methodology, as conveyed in National Institute of Standards and Technology (NIST) Handbook 135 (Kneifel and Webb 2022). This report is intended to provide relatively high-level guidance, acting as a complement to, rather than a substitute for, that resource.
Depending on a range of technical, economic, policy, regulatory, and market-related factors, the adoption of DPV may have a net positive or negative financial impact on utilities and ratepayers. This guidebook provides a methodological approach for quantifying the net financial impact of DPV on utilities (in the form of “net revenue losses”) and ratepayers (in the form of “net tariff impacts”). Written for technical staff at utilities, regulatory bodies, energy ministries, research institutes, and civil society organizations who wish to better understand the financial impacts of DPV in their jurisdiction, this guidebook can be used to inform important decisions regarding DPV compensation, tariff design, and regulatory cost allocations, among other aspects. It is focused exclusively on customer-sited DPV systems and adopts a primarily cost-based (as opposed to an equally valid value-based) perspective to understanding DPV financial impacts. The approach for calculating net revenue losses can be applied in nearly any utility jurisdiction, regardless of institutional arrangements, business models, or regulatory paradigms.
Software inspection is a technical evaluation process for finding and removing defects in requirements, design, code, and tests. Detailed data was collected during the first three years of experience at JPL on 203 inspections. Statistics are discussed for this set of inspections. Included, on a per inspection basis, are averages of: staff time expended, pages covered, major defects found, minor defects found, and inspection team size. Analysis of variance showed a significantly higher density of defects during requirements inspections. It was also observed, that the defect densities found decreased exponentially as the work products approached the coding phase. Increasing the pace of the inspection meeting decreased the density of defects found. This relationship was observed to hold for both major and minor defect densities, although it was more pronounced for minor defects. Guidelines are provided for conducting successful software inspections based upon three years of JPL experience.
The purpose of the Advanced Transportation System Studies (ATSS) Technical Area 2 (TA-2) Heavy Lift Launch Vehicle Development contract was to provide advanced launch vehicle concept definition and analysis to assist NASA in the identification of future launch vehicle requirements. Contracted analysis activities included vehicle sizing and performance analysis, subsystem concept definition, propulsion subsystem definition (foreign and domestic), ground operations and facilities analysis, and life cycle cost estimation. This document is Volume 2 of the final report for the contract. It provides documentation of selected technical results from various TA-2 analysis activities, including a detailed narrative description of the SSTO concept assessment results, a user's guide for the associated SSTO sizing tools, an SSTO turnaround assessment report, an executive summary of the ground operations assessments performed during the first year of the contract, a configuration-independent vehicle health management system requirements report, a copy of all major TA-2 contract presentations, a copy of the FLO launch vehicle final report, and references to Pratt & Whitney's TA-2 sponsored final reports regarding the identification of Russian main propulsion technologies.
The increasing global deployment of wind energy has given rise to concerns about potential adverse effects on certain wildlife species and habitats. The United States and European nations use environmental impact assessments (EIAs) to evaluate the environmental effects of wind energy and inform wind energy planning, siting, and operational processes. A key component of the EIA is the cumulative effects analysis/assessment (CEA). CEAs consider the effects of a proposed development in the context of past, present, and future developments, as well as other (non-wind) activities. However, practitioners worldwide have struggled to implement cost-effective and consistent processes for CEAs. Further, there is no widely accepted scientific methodology to assess cumulative effects. As wind energy deployment continues to expand, developing a consistent and scientifically based approach to CEAs may provide a more comparable across assessments and cost-effective means of reducing risk during siting, operations, and decommissioning/repowering, while minimizing regulatory hurdles. This technical report evaluates the current state of CEA practices, covering both land-based and offshore wind energy development. It focuses on impacts from the preconstruction, construction, and operational phases of the wind farm, which are the phases where most research currently exists. Emerging research addresses impacts from the perspective of life cycle assessments (LCAs), including the impacts of manufacturing and preconstruction (May et al. 2020). The technical report also summarizes CEA processes and guidelines, analysis approaches, and current challenges. Finally, it highlights opportunities for further research and coordination, and includes a geographically organized CEA information resource bank.
The 1992 Life Support Systems Analysis Workshop was sponsored by NASA's Office of Aeronautics and Space Technology (OAST) to integrate the inputs from, disseminate information to, and foster communication among NASA, industry, and academic specialists. The workshop continued discussion and definition of key issues identified in the 1991 workshop, including: (1) modeling and experimental validation; (2) definition of systems analysis evaluation criteria; (3) integration of modeling at multiple levels; and (4) assessment of process control modeling approaches. Through both the 1991 and 1992 workshops, NASA has continued to seek input from industry and university chemical process modeling and analysis experts, and to introduce and apply new systems analysis approaches to life support systems. The workshop included technical presentations, discussions, and interactive planning, with sufficient time allocated for discussion of both technology status and technology development recommendations. Key personnel currently involved with life support technology developments from NASA, industry, and academia provided input to the status and priorities of current and future systems analysis methods and requirements.
Many engineering methods have been developed to help management select technology for a system design or further research. The simplest way to compare technologies is to use a checklist containing all the more or less important selection criteria, so that nothing is overlooked. The criteria usually include cost, safety, reliability and maintainability, and potential problems such as noise generation and microgravity sensitivity. The next step typically is to weight and score all the criteria. The process of weighting and scoring is helpful in bringing out different priorities and reaching a shared point of view. Group technology selection methods are designed to highlight initial disagreements and produce a shared consensus. Often a frank discussion led by management rather than decision analysts can be more effective. The final selection depends on management and engineering judgment and may include programmatic and organizational factors that are beyond the engineering checklist. The objective of engineering technology selection methods is to provide engineering information to assist management in making sound decisions. Project management and technology selection are assumed to use rational engineering analytic methods, but they often do not. The reason is that human insight, intuition, and “gut feel,” rather than logic, more frequently determine our decisions. Project selection and management are strongly influenced by nonrational psychological influences, which can produce unjustified confidence and determination. Nevertheless, there is a strong need for space projects to do rational project analysis and selection. Demonstrating a rational spirit is necessary for a scientific and technical organization. Professional ethics at its best requires an open, honest, and fair process, without damaging politics. Rational analysis can help improve good projects and avoid selecting bad ones. A sanity check using rational analysis guided by a checklist can help avoid egregious and damaging errors.
The Los Alamos National Laboratory (LANL) environmental legacy cleanup program requires decisions to be made for environmental remediation, decommissioning and disposal or management of radioactive waste. This legacy cleanup program was established to address groundwater contamination, material disposal areas (MDAs) that have been used to dispose of radioactive and other waste material, and 'aggregate areas' that might produce radioactive or other chemical waste as a result of remediation activities. The LANL site is regulated for environmental concerns under the Resource Conservation and Recovery Act (RCRA). However, some parts of LANL, such as material disposal area G (MDA G), have disposed of radioactive waste under DOE Order 435.1, and are subject to other regulations. For example, decommissioning the remote-handled TRU material stored in 33 shafts at MDA G falls under EPA's 40 CFR 191. Collectively, the regulations are all aimed in the same direction of finding the best solution, either through constructs such as 'as low as reasonably achievable' (ALARA), considering balancing factors as opposed to only cost and human health risk, and, under EPA regulations such as RCRA and NEPA, evaluating impact from all chemicals and both human health and ecological endpoints. Despite the basic goals and objectives of the regulations or their guidance, the main challenge is in their implementation. Arguably perhaps, but really in principle, all of these (and similar) regulations are asking for a decision analysis to be performed. Implementation challenges encountered have included lack of understanding of decision analysis in the industry, lack of effective stakeholder engagement in the decision analysis process, and lack of appreciation of the need to separate value judgments from science, the latter leading to developing conservative, or protective, science-based models. Conservative models lead to poor solutions, lack of effective stakeholder engagement leads to long drawn out protracted approaches to finding a solution (which also might never be found with this approach), and lack of understanding of decision analysis and Bayesian statistics causes poor models to be built, which creates unfortunate situations of 'garbage in, garbage out' becoming the basis for decision making. Stakeholder-engaged structured decision making (SDM) is an approach to solving problems that relies on the theory of decision science to involve stakeholders in the decision-making process. This approach incorporates stakeholder values using a scientifically rigorous methodology that separates value judgments from science in a way that helps avoid the pitfalls of biased, protective, or conservative modeling. This approach has its foundation in Keeney's 1992 treatise on value-focused thinking [1]. Keeney advocated a paradigm shift in decision making based on the idea that the standard way of thinking about decisions is backwards. The standard approach of focusing first on identifying alternatives rather than on articulating values results in a reactive approach with the emphasis on mechanics and fixed choices instead of the core values that have meaning to stakeholders. This paradigm shift effectively engages all stakeholders in the decision-making process while using a values focused thinking approach that can lead to the identification of decision opportunities and the creation of better alternatives. The intent is to be proactive and generate solutions that are related directly to values and objectives as identified by stakeholders. There are, perhaps, two overarching reasons why SDM can be used to benefit LANL's environmental legacy cleanup. Some of LANL's remaining waste management and environmental management problems are challenging and complex (for example, the Cr and RDX plumes, and MDAs) and while the traditional approach has, arguably, worked well for relatively simple risk-based problems, it cannot, or should not, be applied to more complex problems if the most effective and efficient solutions are desired. The second reason is cost. This has perhaps become more critical since publication of the Government Accountability Office (GAO) reports that DoE's environmental liability is considered a high-risk concern for the nation [2]. The focus of SDM is on structuring solutions to decision risk problems by first addressing stakeholder and decision maker values and subsequently developing decision objectives and ways to measure those objectives, preference weighting across objectives, identifying decision alternatives that best achieve those values, and characterizing uncertainty in predictions of the measures. Because a complete decision model is created using SDM, it can be evaluated to find the main elements of the model that drive, or predict, the best solution. This approach creates complete decision models that are transparent, traceable, reproducible and technically defensible. The science behind SDM, or decision analysis, is well founded, yet it is not unusual to see ad hoc approaches to decision making implemented under various environmental regulations that are pertinent to the LANL site, including NEPA, RCRA and DOE Order 435.1. Such ad hoc approaches are often not transparent or traceable, and lack reproducibility and technical defensibility. The LANL legacy cleanup program has embarked on using SDM to address the complex problems that remain. Stakeholder meetings have been held, and a prototype version of the stakeholder value system has been developed. Further meetings are expected in the future to address specific project needs. This is a long-term endeavor considering the complex environmental problems faced by DOE EM in Los Alamos (EM-LA), and careful planning, consideration of stakeholder value systems, and engagement with stakeholders throughout the SDM process is expected to lead to a successful endpoint. (authors)
The United States nuclear industry is facing a strong challenge to ensure maximum safety while enhancing economic benefit. Safety is a key parameter to all aspects related to light water reactor (LWR) nuclear power plants (NPPs), especially cost savings. Since the goal is to extend the lifetimes of these NPPs, the traditional deterministic safety concept may not guarantee a current economic asset. The Light Water Reactor Sustainability (LWRS) Program has been promoting a wide range of research and development (R&D) in this field to maximize the safety, economics, and performance of these NPPs through improved scientific understanding. One of the best practices to achieve this goal is to identify and optimize safety margins, which can lead to cost reduction. To do this, under the LWRS framework, the Risk-Informed Systems Analysis (RISA) Pathway will focus on the optimization of safety margin and minimization of uncertainties to ensure both safety and economics at the highest level. The RISA Pathway will provide enhanced capabilities for analyzing and characterizing LWR systems performance by developing and demonstrating methods, tools, and data to enable risk-informed margins management (RIMM). The goals of the RISA Pathway are twofold: (1) deploy the risk-informed tools and methods that enable better representation of safety margins and factors that contribute to cost and safety; and (2) conduct advanced risk assessment applications with industry to support margin management strategies that enable more cost-effective plant operation. The tools and methods provided by the RISA Pathway will support effective margin management for both active and passive safety systems, structures, and components (SSC) of an NPP. The tools and methods used in the RISA Pathway should have high confidence and highest technical maturity for and implementation to industry at its current setting. They should also have a capability to support risk-informed decision making for both probabilistic and deterministic elements of safety. The RISA Pathway will, therefore, perform a comprehensive assessment of verification and validation (V&V) status of RISA Toolkit to enhance credibility RISA Toolkit which be used by industry. This report summarizes assessment technical maturity of RISA thermal-hydraulics accident analysis code RELAP5-3D and multi-purpose probabilistic risk analysis tool RAVEN V&V status including specific information of the tool such as capability and features, quality assurance program, developer/independent V&V record, separation/integral tests history, user documents, and feedback.