Search NASA⌕ Search

SEARCH · Search NASA

Results for “portfolio management”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

BETTER Together

The Standard Energy Efficiency Data (SEED) and Building Efficiency Targeting Tool for Energy Retrofits (BETTER) platforms are both developed by the Department of Energy and work better together. SEED is a database to manage building characteristics and performance data from a variety of sources. BETTER provides simple energy efficiency measure analyses based on high level data about the building or portfolio of buildings. A demonstration of each platform and their integration will be provided. The inputs for BETTER are building type, floor area, location, utility data, and whether PV shall be included in the analysis. The BETTER analysis can be manually set up through the web application or data can be uploaded with a BuildingSync XML file either directly or through the API. SEED can be the source of this data and the data can be sent to BETTER through the SEED application after the BETTER API token has been entered. The benefit of utilizing SEED is that it has connections to many other sources of data such as ENERGY STAR Portfolio Manager, Audit Template, and Salesforce. Therefore, it is likely that a user of SEED will already have the required inputs for BETTER in SEED already and can create BETTER analyses across their whole portfolio in a couple mouse clicks. This is a major time savings and enables decision makers an easy path to identify buildings that should undergo more detailed audits or retrofit pathways.

ASHRAE↗
NASA NTRS2017

Radioisotope Power Systems Program Status and Expectations

The Radioisotope Power Systems (RPS) Programs goal is to make RPS available for the exploration of the solar system in environments where conventional solar or chemical power generation is impractical or impossible to use to meet mission needs. To meet this goal, the RPS Program manages investments in RPS system development and RPS technologies. The RPS Program exists to support NASA's Science Mission Directorate (SMD). The RPS Program provides strategic leadership for RPS, enables the availability of RPS for use by the planetary science community, successfully executes RPS flight projects and mission deployments, maintains a robust technology development portfolio, manages RPS related National Environmental Policy Act (NEPA) and Nuclear Launch Safety (NLS) approval processes for SMD, maintains insight into the Department of Energy (DOE) implementation of NASA funded RPS production infrastructure operations, including implementation of the NASA funded Plutonium-238 production restart efforts. This paper will provide a status of recent RPS activities.

Radioisotope↗
NASA NTRSDate not supplied

NASA’s Developments in Cryogenic Fluid Management Technology

NASA has been pursuing the development and demonstration of enabling and enhancing technologies for Cryogenic Fluid Management (CFM) in collaboration with the US industry. NASA’s vision for current and future space exploration requires high-performance chemical and nuclear propulsion solutions that utilize cryogens. The Agency will use cryogenic fluids for Earth-to-orbit transportation, human missions to the Moon and Mars, planetary exploration, and in-situ resource utilization (ISRU) production. All these architectures will require state-of-the-art long-duration storage on the surface and in-space transfer for refueling. This paper focuses on key CFM technology developments completed or ongoing by the Cryogenic Fluid Management Portfolio Office within NASA’s Space Technology Mission Directorate. The CFM Portfolio Office, partnered with US aerospace industry, has invested in CFM technology ground and flight demonstrations, focused on maturing CFM hardware and operations for Artemis and Moon to Mars activities. These demonstrations additionally provide NASA with data to inform numerical modeling activities for verification and validation of design tools and approaches for future missions. This paper includes discussion on remaining high-priority open CFM technology gaps for Mar-forward architectures and initiatives for closure.

Cryogenic Fluid Management↗
NASA NTRS2012

Integration of Linear Dynamic Emission and Climate Models with Air Traffic Simulations

Future air traffic management systems are required to balance the conflicting objectives of maximizing safety and efficiency of traffic flows while minimizing the climate impact of aviation emissions and contrails. Integrating emission and climate models together with air traffic simulations improve the understanding of the complex interaction between the physical climate system, carbon and other greenhouse gas emissions and aviation activity. This paper integrates a national-level air traffic simulation and optimization capability with simple climate models and carbon cycle models, and climate metrics to assess the impact of aviation on climate. The capability can be used to make trade-offs between extra fuel cost and reduction in global surface temperature change. The parameters in the simulation can be used to evaluate the effect of various uncertainties in emission models and contrails and the impact of different decision horizons. Alternatively, the optimization results from the simulation can be used as inputs to other tools that monetize global climate impacts like the FAA s Aviation Environmental Portfolio Management Tool for Impacts.

Sridhar, Banavar↗
NASA NTRS2023

NASA Team Develops a Test Article to Demonstrate “Zero Boil-Off” Storage of Liquid Hydrogen via Cryocoolers and a Two-Stage Cooling Approach

Funded by NASA’s Technology Demonstration Mission Program and managed by the Cryogenic Fluid Management Portfolio Project, a NASA team is developing a test article to demonstrate the “zero boil-off” storage of liquid hydrogen using active cooling (cryocoolers) and a two-stage cooling approach. The current state of the art for storage of liquid hydrogen on-orbit is on the order of hours while future missions may require storage for months or even years. To enable such extended storage durations, “near zero” propellant loss, or “zero boil-off”, must be achieved. This may be accomplished with the implementation of “near zero” leakage components, a high performing suite of passive technologies to minimize the environmental heat loads, and active cooling via cryocoolers to intercept and remove heat from the propellant tanks and associated structure. Of course, with any cryogenic vehicle and mission, a mass and power trade should be conducted to determine if it is indeed feasible to carry the additional dry mass associated with active cooling, or if one could simply carry additional propellants to accommodate propellant loss which is typically not an option for a long duration mission.

Hydrogen Storage↗
NASA NTRS2015

Simulation and Analysis of Technology and Operational Procedures to Reduce the Combined Effects of Emissions and Contrails

The development and evaluation of concepts and technology to support future air traffic management systems require a hierarchy of models ranging from real-time simulations to extensive field evaluations. Air traffic simulation models such as Airspace Concept Evaluation System, Center Tracon Automation System, Future Air traffic management Concept Evaluation Tool and others are used to design air traffic systems balancing the conflicting objectives of maximizing safety, meeting future demands for airports and airspace and increase efficiency of traffic flows in the presence of uncertain weather. The impact of aviation emissions and contrails on climate imposes another constraint on the design of aircraft and aviation operations. The understanding of the complex interaction between physical climate system, the carbon and other greenhouse gas emissions and aviation activity can be improved by the development of integrated assessment models that include emission and climate models together with air traffic simulations. The modeling of aircraft emissions and their interaction with each other to change the concentration levels of different gasses in the atmosphere and the resulting impact of the radiative forcing on the equilibrium of the Earth's atmosphere is complex and requires the use of coupled atmosphere-ocean general circulation models together with three-dimensional models of carbon cycle and chemistry of other non-CO2 greenhouse gases. These models are computationally intensive and unsuitable for studies involving the generation of multiple scenarios. Simple emission and climate models, based on the input-output relations of linear systems, capture the fundamental emission to climate impact behavior by careful selection of key variables and their dynamics. The impact of various greenhouse gases depends on the total concentration, effect per unit change in atmospheric concentration and the spatial distribution of the gas. All these quantities are influenced by the lifetime of the gas. The impact of a greenhouse gas depends on the interval of assessment, which may vary from a few decades to a few centuries. Climate metrics are aimed at providing a common scale to compare different greenhouse gases. If the metrics are to be used as a tool in developing and evaluating aviation operations, they should be transparent and easy to apply. Global Warming Potential and Aggregate Global Temperature Potential are some of the commonly used metrics. This paper integrates a national-level air traffic simulation and optimization capability with simple climate models and carbon cycle models, and climate metrics to assess the impact of aviation on climate. The capability brings together metrics, which are useful in aviation operations together with metrics used in climate studies. The capability can be used to make trade-offs between extra fuel cost and reduction in climate impact. There is considerable uncertainty in our understanding of the radiative forcing associated with emissions and contrails. The parameters in the simulation can be used to evaluate the effect of various uncertainties in emission models and contrails. It can also be used to evaluate the impact of different decision horizons. Alternatively, the optimization results from the simulation can be used as inputs to other tools that monetize global climate impacts like the FAA's Aviation Environmental Portfolio Management Tool for Impacts.

impact of aviation on the environment↗
DOE OSTI2022

pnnl/portfoliomanager-rb

This invention is a Ruby "gem" (library) that provides clients for ENERGY STAR Portfolio Manager (ESPM) Web Services, Inventive features: 100% coverage of version 18.0 of the ESPM API. Automated mapping between ESPM XML schemas and Ruby objects. Clients for both the "live" and "test" ESPM API environments. Debugging mode with HTTP request/response logging.

Borkum, Mark↗
NASA NTRS2008

Systems Engineering: When Knowledge and Technology are the Product

The interdependence of technology development, conceptual design, and system analysis is examined in the context of an overall systems engineering set of processes. In particular, the role of technology portfolio management - from initial investment decision-making all the way through technology maturation and transfer to industry - is emphasized. Additionally, the role of state of the art assessments is considered in terms of planning and tracking progress towards the development of enhanced predictive capabilities.

Young, Larry A.↗
NASA NTRS2014

Concepts to Support HRP Integration Using Publications and Modeling

Initial efforts are underway to enhance the Human Research Program (HRP)'s identification and support of potential cross-disciplinary scientific collaborations. To increase the emphasis on integration in HRP's science portfolio management, concepts are being explored through the development of a set of tools. These tools are intended to enable modeling, analysis, and visualization of the state of the human system in the spaceflight environment; HRP's current understanding of that state with an indication of uncertainties; and how that state changes due to HRP programmatic progress and design reference mission definitions. In this talk, we will discuss proof-of-concept work performed using a subset of publications captured in the HRP publications database. The publications were tagged in the database with words representing factors influencing health and performance in spaceflight, as well as with words representing the risks HRP research is reducing. Analysis was performed on the publication tag data to identify relationships between factors and between risks. Network representations were then created as one type of visualization of these relationships. This enables future analyses of the structure of the networks based on results from network theory. Such analyses can provide insights into HRP's current human system knowledge state as informed by the publication data. The network structure analyses can also elucidate potential improvements by identifying network connections to establish or strengthen for maximized information flow. The relationships identified in the publication data were subsequently used as inputs to a model captured in the Systems Modeling Language (SysML), which functions as a repository for relationship information to be gleaned from multiple sources. Example network visualization outputs from a simple SysML model were then also created to compare to the visualizations based on the publication data only. We will also discuss ideas for building upon this proof-of-concept work to further support an integrated approach to human spaceflight risk reduction.

Mindock, J.↗
NASA NTRS2015

Enhancing Interdisciplinary Human System Risk Research Through Modeling and Network Approaches

NASA's Human Research Program (HRP) supports research to reduce human health and performance risks inherent in future human space exploration missions. Understanding risk outcomes and contributing factors in an integrated manner allows HRP research to support development of efficient and effective mitigations from cross‐disciplinary perspectives, and to enable resilient human and engineered systems for spaceflight. The purpose of this work is to support scientific collaborations and research portfolio management by utilizing modeling for analysis and visualization of current and potential future interdisciplinary efforts.

Mindock, Jennifer↗
NASA NTRSDate not supplied

Development of a Test Article to Demonstrate the Long Duration Storage of Liquid Hydrogen via a Two-Stage Active Cooling Approach

A NASA team is developing a test article for the purpose of demonstrating the long duration storage of liquid hydrogen utilizing passive Cryogenic Fluid Management and cryocoolers via a two-stage active cooling approach. Funded by NASA’s Technology Demonstration Mission Program and managed by the Cryogenic Fluid Management Portfolio Project, the team is leveraging demonstrations conducted under pervious NASA activities to develop a fully integrated test article that will demonstrate the zero boil-off storage of liquid hydrogen. This paper discusses the previous activities being leveraged from NASA’s Cryogenic Propellant Storage and Transfer project, the test article design and build, hardware and instrumentation selections, control methodology, and the planned primary and secondary test objectives. The test article assembly and demonstration are both to be conducted in the East Test Area at NASA Marshall Space Flight Center and are currently scheduled for Fiscal Year 2024.

Active Cooling↗
DOE OSTI2022

Better bang for your buck? Comparing savings realization from ESPCs and direct-funded projects

Energy savings performance contracts (ESPCs) offer an opportunity to tremendously scale decarbonization projects, given their paid-from-savings premise. However, prospective customers still question whether ESPC is worth the effort and expense. This study evaluates the savings realization rates of ESPCs compared to direct-funded projects using ENERGY STAR Portfolio Manager (ESPM) benchmarking data. It compares normalized EUIs from ESPM before and after energy conservation projects implemented via ESPC or direct funding in roughly 450 federal buildings. This documented change, ideally a savings, can then be compared to the estimated savings from the energy conservation initiative in order to generate a rough realization rate. Preliminary results indicate a notably greater savings realization rate for the ESPC buildings (median = 105% of estimated savings) than those that underwent direct-funded projects (median = 46%). Because of a shortage of good quality data and the wide range in results, the difference is only significant at the p < 0.20 level. However, the higher savings realization of ESPCs corroborates the authors’ 2014 findings using a different comparison method. With continued soft government funding and regulatory impediments for climate change mitigation in the U.S., financed, paid-from-savings project models (e.g., ESPC, PACE, EaaS and others) certainly merit more attention. This study’s results are particularly compelling (and encouraging) given the country’s likely reliance on these vehicles to address existing building retrofits.

Earni, Shankar↗
DOE OSTI2024

Equitable Energy Metrics for Integration into Building Performance Standard Tracking Platforms: Preprint

Building Performance Standards (BPS) are being adopted globally and in the United States of America, where 14 different states and jurisdictions have a policy in place and many others are under development (Department of Energy (DOE) 2023). Accurate and equitable data sources are essential to make informed decisions about focusing investment on upgrading buildings to meet jurisdictional goals. There have been multiple new tools developed related to Energy Equity and Environmental Justice (EEEJ) and the resulting datasets need to be integrated into large building port-folios for quick access and better scalability. Integrating EEEJ data in a user-friendly format can help decision makers more quickly assess impacts and analyze the multitude of potentially significant metrics for which there is not yet consensus. In the U.S. and Canada, many BPS ordinances rely primarily on ENERGY STAR Portfolio Manager (ESPM) to capture building characteristics and energy and water consumption data. These datasets can then be imported into city-specific building tracking tools like the Standard Energy Efficiency Data Platform (SEED). Crucially, BPS decision makers require an efficient means of identifying buildings in priority communities to effectively allocate resources and funding. This process must integrate seamlessly with existing jurisdictional toolsets for optimal utility. This paper will demonstrate, for the case of Washington D.C.'s (the District) data, a workflow that provides actionable data for building upgrade investment prioritization in disadvantaged communities.

BPS↗
DOE OSTI2026

Machine Learning Based Metamodel for Faster Life Cycle Assessment of Large Portfolio of Buildings

Managing a large portfolio of buildings involves decisions on reuse, retrofit, renovation, rehabilitation, and new construction, influenced by trade-offs between performance metrics such as cost, time, and operational flexibility over the building's life cycle. Traditional life cycle assessment tools for evaluating these metrics can be labor- and compute-intensive, requiring extensive data and modeling for each building. Metamodels (or surrogate models) using machine learning have been explored as faster alternatives, but training these models has been hindered by the limited availability of comprehensive data on key life cycle metrics. Recent advancements in machine learning, particularly deep learning techniques like zero-shot and few-shot learning, allow models to learn from sparse or limited data. We propose a machine learning-based metamodel that leverages these techniques for rapid estimation of key building life cycle metrics. This presentation will cover the model architecture, data collection, training, and validation processes, along with an ongoing case study applied to a large portfolio of buildings. We will discuss the model's performance in terms of accuracy, compute time, limitations, and its potential for expanding to additional life cycle metrics. This data-driven approach offers a promising direction for the rapid evaluation of large building portfolios.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2010

Risk Assessment and Integration Team (RAIT) Portfolio Risk Analysis Strategy

Impact at management level: Qualitative assessment of risk criticality in conjunction with risk consequence, likelihood, and severity enable development of an "investment policy" towards managing a portfolio of risks. Impact at research level: Quantitative risk assessments enable researchers to develop risk mitigation strategies with meaningful risk reduction results. Quantitative assessment approach provides useful risk mitigation information.

Edwards, Michelle↗
DOE OSTI2024

An exploration of online-simulation-driven portfolio scheduling in Workflow Management Systems

Workflow Management Systems used to automate the execution of scientific workflow applications on parallel and distributed computing platforms must make scheduling decisions at runtime. A large number of workflow scheduling algorithms have been proposed in the literature, but often these algorithms are evaluated based on simplifying assumptions that may not hold in practice. Furthermore, published algorithm evaluation and/or comparison results are necessarily only for a subset of all possible scenarios, and thus may not include scenarios relevant to particular use-cases. Consequently, it is difficult for Workflow Management Systems (WMSs) developers to decide which scheduling algorithm should be implemented. To obviate this difficulty, one possible approach is to implement a portfolio of scheduling algorithms and select the most effective algorithm at runtime. One method for performing this selection is to run an online simulation for each algorithm in the portfolio. The algorithm that leads to the best performance, in simulation, is selected for future use. The above simulation-driven portfolio scheduling (SDPS) approach has been proposed in a few parallel and distributed computing contexts. The main objective of this work is to evaluate the feasibility and potential merit of SDPS if implemented in WMSs. Here we perform this evaluation using simulated WMS executions, where the simulations are instantiated from real-world platform and workflow configurations. Our main finding is that SDPS is on par with or outperforms an approach in which a single algorithm is used, where this algorithm is the one that performs best on average across all our experimental scenarios. Furthermore, we find that SDPS remains an attractive proposition even in the presence of high levels of simulation error and for simulators with relatively low levels of sophistication. In many of our experimental scenarios we find that mitigating simulation error at runtime can further improve performance. Finally, we show that simulation overhead can be made sufficiently low for SDPS to be feasible in practice.

97 MATHEMATICS AND COMPUTING↗