Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Frameworks”

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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Framework for Modeling High-Impact, Low-Frequency Power Grid Events to Support Risk-Informed Decisions

Natural and man-made hazardous events resulting in loss of grid infrastructure assets challenge the electric power grid’s security and resilience. However, the planning and allocation of appropriate contingency resources for such events requires an understanding of their likelihood and the extent of their potential impact. Where these events are of low likelihood, a risk-informed perspective on planning can be problematic as there exists an insufficient statistical basis to directly estimate the probabilities and consequences of their occurrence. Since risk-informed decisions rely on such knowledge, a basis for modeling the risk associated with high-impact low frequency events (HILFs) is essential. Insights from such a model can inform where resources are most rationally and effectively expended. The present effort is focused on development of a HILF risk assessment framework. Such a framework is intended to provide the conceptual and overarching technical basis for the development of HILF risk models that can inform decision makers across numerous stakeholder sectors. The North American Electric Reliability Corporation (NERC) 2014 Standard TPL-001-4 considers severe events for transmission reliability planning, but does not address events of such severity that they have the potential to fail a substantial fraction of grid assets over a region, such as geomagnetic disturbances (GMD), extreme seismic events, and coordinated cyber-physical attacks. These are beyond current planning guidelines. As noted, the risks associated with such events cannot be statistically estimated based on historic experience; however, there does exist a stable of risk modeling techniques for rare events that have proven of value across a wide range of engineering application domains. There is an active and growing interest in evaluating the value of risk management techniques in the State transmission planning and emergency response communities, some of this interest in the context of grid modernization activities. The availability of a grid HILF risk model, integrated across multi-hazard domains which, when interrogated, can support transparent, defensible and effective decisions, is an attractive prospect among these communities. In this report, we document an integrated HILF risk framework intended to inform the development of risk models. These models would be based on the systematic and comprehensive (to within scope) characterization of hazards to the level of detail required for modeling risk, identification of the stressors associated with the hazards (i.e., the means of impacting grid and supporting infrastructure), characterization of the vulnerability of assets to these stressors and the probabilities of asset compromise, the grid’s dynamic response to the asset failures, and assessment of subsequent severities of consequence with respect to selected impact metrics, such as power outage duration and geographic reach. Specifically, the current framework is being developed to;1. Provide the conceptual and overarching technical paradigms for the development of risk models; 2. Identify the classes of models required to implement the framework - providing examples of existing models, and also identifying where modeling gaps exist; 3. Identify the types of data required, addressing circumstances under which data are sparse and the formal elicitation of informed judgment might be required; and 4. Identify means by which the resultant risk models might be interrogated to form the necessary basis for risk management.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2019

Defining a Space Mission Architectural Framework: Guiding Robotic Space Mission Design and Development at NASA Goddard Spaceflight Center

Modern Systems Engineering activities for robotic science missions face increased complexity due to evolving measurement requirements, increased collaboration amongst stakeholders and increased collaboration between human and robotic systems. While NASA has employed standard process frameworks for project management and systems engineering for years, it has not yet established an architecture framework (AF) by which its mission systems are described. While an architecture framework is not a necessary component of an organization's operations, the value of a specified AF greatly enhances an organization's ability to define systems consistently and aid in communication across project and organizational boundaries. The current effort identifies an approach to establishing a Space Mission Architecture Framework (SMAF), an AF with roots in ISO 42010 (Systems and Software Engineering-Architecture Description), NASA Procedural Requirements (NPR) 7120.5 (NASA Space Flight Program and Project Management Requirements) and 7123.1B (NASA Systems Engineering Processes and Requirements). The heart of the AF lies in its viewpoints and work products, artifacts that represent a set of information from the viewpoint of a particular stakeholder. This effort articulates the needs, goals and objectives that the SMAF addresses, as well as the approach to creating the framework and establishing the various work products. A full set of work products, sufficient to satisfy the Mission System reporting requirements of NPR 7120/7123 at Key Decision Point (KDP) A is identified in this paper.

Architecture↗
DOE OSTI2014

Site transition framework for long-term surveillance and maintenance

This document provides a framework for all U.S. Department of Energy (DOE) facilities and sites where DOE may have anticipated long-term surveillance and maintenance (LTSM) responsibilities. It is a tool to help facilitate a smooth transition from remediation to LTSM, providing a systematic process for affected parties to utilize in analyzing the baseline to understand and manage the actions from EM mission completion through a site’s transition into LTSM. The framework is not meant to provide an exhaustive list of the specific requirement and information that are needed. Sites will have unique considerations that may not be adequately addressed by this tool, and it is anticipated that a team comprised of the transferring and receiving organization will use judgment in utilizing this augmenting with other DOE guidance. However the framework should be followed to the extent possible at each site; and adapted to accommodate unique site-specific requirements, needs, and documents. Since the objective of the tool is facilitate better understanding of the conditions of the site and the actions required for transfer, the transition team utilizing the checklist is expected to consult with management of both the receiving and transferring organization to verify that major concerns are addressed. Ideally, this framework should be used as early in the remediation process as possible. Subsequent applications of the Site Transition Framework (STF) to the site should be conducted periodically and used to verify that all appropriate steps have been or will be taken to close-out the site and that actions by both organization are identified to transfer the site to LTSM. The requirements are provided herein.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2013

A technical framework to describe occupant behavior for building energy simulations

Green buildings that fail to meet expected design performance criteria indicate that technology alone does not guarantee high performance. Human influences are quite often simplified and ignored in the design, construction, and operation of buildings. Energy-conscious human behavior has been demonstrated to be a significant positive factor for improving the indoor environment while reducing the energy use of buildings. In our study we developed a new technical framework to describe energy-related human behavior in buildings. The energy-related behavior includes accounting for individuals and groups of occupants and their interactions with building energy services systems, appliances and facilities. The technical framework consists of four key components: i. the drivers behind energy-related occupant behavior, which are biological, societal, environmental, physical, and economical in nature ii. the needs of the occupants are based on satisfying criteria that are either physical (e.g. thermal, visual and acoustic comfort) or non-physical (e.g. entertainment, privacy, and social reward) iii. the actions that building occupants perform when their needs are not fulfilled iv. the systems with which an occupant can interact to satisfy their needs The technical framework aims to provide a standardized description of a complete set of human energy-related behaviors in the form of an XML schema. For each type of behavior (e.g., occupants opening/closing windows, switching on/off lights etc.) we identify a set of common behaviors based on a literature review, survey data, and our own field study and analysis. Stochastic models are adopted or developed for each type of behavior to enable the evaluation of the impact of human behavior on energy use in buildings, during either the design or operation phase. We will also demonstrate the use of the technical framework in assessing the impact of occupancy behavior on energy saving technologies. The technical framework presented is part of our human behavior research, a 5-year program under the U.S. - China Clean Energy Research Center for Building Energy Efficiency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Cyber Threat Dictionary Using MITRE ATT&CK Matrix and NIST Cybersecurity Framework Mapping

Cyber-attack and defense frameworks offer numerous ways to protect systems and networks from threats. However, only a few of these numerous attack and defense frameworks provide countermeasures by linking multiple frameworks. Due to the lack of attack-defense mapped frameworks, a number of cyber security practitioners are often puzzled how to cope with cyber-attacks when it occurs. The objective of this paper is to present a tool called the “Cyber Threat Dictionary” to solve the problem . Cyber Threat Dictionary offers approaches and practical solutions to the threats by mapping MITRE ATT&CK Matrix to the NIST Cybersecurity Framework. By providing immediate solutions to cyber security practitioners, Cyber Threat Dictionary enables effective responses against cyber-attacks.

MITRE ATT&CK MATRIX, NIST Cybersecurity Framework,↗
DOE OSTI2023

Developing an AI-Powered Zero-Trust Cybersecurity Framework for Malware Prevention in Nuclear Power Plants

This study presents the development of an AI-powered Zero-Trust cybersecurity framework for malware prevention in nuclear power plants. The framework aims to enhance the security of critical systems within nuclear power plants by adopting the principles of Zero-Trust and leveraging artificial intelligence (AI) technologies. By assuming no implicit trust in any user or device and continuously authenticating and authorizing access, the framework ensures a robust defense against malware attacks. The integration of AI allows for the detection and prevention of malware through behavioral analytics, endpoint protection, network segmentation, and continuous monitoring. The paper discusses the key considerations, steps, and technologies involved in developing this framework, emphasizing the importance of regular updates, training, compliance, and auditing. The proposed framework serves as a comprehensive approach to safeguarding nuclear power plants from sophisticated malware threats and protecting the integrity and safety of critical infrastructure.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Ce IV 70 Oxosulfate Rings, Frameworks, Supramolecular Assembly, and Redox Activity**

Abstract M IV molecular oxo‐clusters (M=Zr, Hf, Ce, Th, U, Np, Pu) are prolific in bottoms‐up material design, catalysis, and elucidating reaction pathways in nature and in synthesis. Here we introduce Ce 70 , a wheel‐shaped oxo‐cluster, [Ce IV 70 (OH) 36 (O) 64 (SO 4 ) 60 (H 2 O) 10 ] 4− . Ce 70 crystallizes into intricate high pore volume frameworks with divalent transition metals and Ce‐monomer linkers. Eight crystal‐structures feature four framework types in which the Ce 70 ‐rings are linked as propellers, in offset‐stacks, in a tartan pattern, and as isolated rings. Small‐angle X‐ray scattering of Ce 70 dissolved in butylamine, with and without added cations (Ce IV , alkaline earths, Mn II ), shows the metals‘ differentiating roles in ring linking, leading to supramolecular assemblies. The large acidic pores and abundant terminal sulfates provide ion‐exchange behavior, demonstrated with U IV and Nd III . Frameworks featuring Ce III/IV ‐monomer linkers demonstrate both oxidation and reduction. This study opens the door to mixed‐metal, highly porous framework catalysts, and new clusters for metal‐organic framework design

Colliard, Ian↗
DOE OSTI2021

Ce IV 70 oxosulfate rings, frameworks, supramolecular assembly and redox activity

M IV molecular oxo-clusters (M=Zr, Hf, Ce, Th, U, Np, Pu) are prolific in bottoms-up material design, catalysis, and elucidating reaction pathways in nature and in synthesis. Here we introduce Ce 70 , a wheel-shaped oxo-cluster, [Ce IV 70 -(OH) 36 (O) 64 (SO 4 ) 60 (H 2 O) 10 ] 4- . Ce 70 crystallizes into intricate high pore volume frameworks with divalent transition metals and Ce-monomer linkers. Eight crystal-structures feature four framework types in which the Ce 70 -rings are linked as propellers, in offset-stacks, in a tartan pattern, and as isolated rings. In this work, small-angle X-ray scattering of Ce 70 dissolved in butylamine, with and without added cations (Ce IV , alkaline earths, Mn II ), shows the metals‘ differentiating roles in ring linking, leading to supramolecular assemblies. The large acidic pores and abundant terminal sulfates provide ion-exchange behavior, demonstrated with U IV and Nd III . Frameworks featuring Ce III/IV -monomer linkers demonstrate both oxidation and reduction. Furthermore, this study opens the door to mixed-metal, highly porous framework catalysts, and new clusters for metal-organic framework design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

From Coordination Cages to a Stable Crystalline Porous Hydrogen-Bonded Framework

A stable framework has been constructed through multiple charge-assisted H-bonds between cationic coordination cages and chloride ions. The framework maintained its original structure upon desolvation, which has been established by single-crystal structure analysis. This is the first fully characterized stable porous framework based on coordination cages after desolvation, with a moderately high Brunauer–Emmett–Teller (BET) surface area of 1201 m2 g-1. This work will not only give a light to construct stable porous frameworks based on coordination cages and thus broaden their applications, but will also provide a new avenue to the assembly of other porous materials such as porous organic cages and hydrogen-bonded organic frameworks (HOFs) through non covalent bonds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A multidimensional stability framework enhances interpretation and comparison of carbon cycling response to disturbance

Abstract The concept of stability is central to the study and sustainability of vital ecosystem goods and services as disturbances increase globally. While ecosystem ecologists, including carbon (C) cycling scientists, have long‐considered multiple dimensions of disturbance response, our discipline lacks an agreed‐upon analytical framework for characterizing multidimensional stability. Here, we advocate for the broader adoption of a standardized and normalized multidimensional stability framework for analyzing disturbance response. This framework includes four dimensions of stability: the degree of initial change in C fluxes (i.e., resistance ); rate (i.e., resilience ) and variability (i.e., temporal stability ) of return to pre‐disturbance C fluxes; and the extent of return to pre‐disturbance C fluxes (i.e., recovery ). Using this framework, we highlight findings not readily seen from analysis of absolute fluxes, including trade‐offs between initial and long‐term C flux responses to disturbance; different overall stability profiles among fluxes; and, using a pilot dataset, similar relative stability of net primary production following fire and insect disturbances. We conclude that ecosystem ecologists’ embrace of a unifying multidimensional stability framework as a complement to approaches focused on absolute C fluxes could advance global change research by aiding in the novel interpretation, comprehensive synthesis, and improved forecasting of ecosystems’ response to an increasing array of disturbances.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Online anomaly detection for multi‐source VMware using a distributed streaming framework

Summary Anomaly detection refers to the identification of patterns in a dataset that do not conform to expected patterns. Such non‐conformant patterns typically correspond to samples of interest and are assigned to different labels in different domains, such as outliers, anomalies, exceptions, and malware. A daunting challenge is to detect anomalies in rapid voluminous streams of data. This paper presents a novel, generic real‐time distributed anomaly detection framework for multi‐source stream data. As a case study, we investigate anomaly detection for a multi‐source VMware‐based cloud data center, which maintains a large number of virtual machines (VMs). This framework continuously monitors VMware performance stream data related to CPU statistics (e.g., load and usage). It collects data simultaneously from all of the VMs connected to the network and notifies the resource manager to reschedule its CPU resources dynamically when it identifies any abnormal behavior from its collected data. A semi‐supervised clustering technique is used to build a model from benign training data only. During testing, if a data instance deviates significantly from the model, then it is flagged as an anomaly. Effective anomaly detection in this case demands a distributed framework with high throughput and low latency. Distributed streaming frameworks like Apache Storm, Apache Spark, S4, and others are designed for a lower data processing time and a higher throughput than standard centralized frameworks. We have experimentally compared the average processing latency of a tuple during clustering and prediction in both Spark and Storm and demonstrated that Spark processes a tuple much quicker than storm on average. Copyright © 2016 John Wiley & Sons, Ltd.

Solaimani, Mohiuddin↗
DOE OSTI2020

A systematic feature extraction and selection framework for data-driven whole-building automated fault detection and diagnostics in commercial buildings

In data-driven automated fault detection and diagnostics (AFDD) modeling for building energy systems, feature engineering is a critical process of extracting information from high-dimensional and noisy sensor measurement and turning it into informative and representative inputs or features for data-driven modeling. However, few studies specifically discuss the feature engineering, especially the interactions between feature extraction and feature selection in whole-building AFDD. We developed a systematic feature extraction and selection framework for whole-building AFDD. In this framework, features are aggressively extracted from raw sensor data using statistical feature extraction techniques with various window sizes and statistics. With many features extracted, a hybrid feature selection algorithm that combines the filter and wrapper method then selects the best feature set. The framework considers diversity in the duration of fault behavior among fault types in whole-building AFDD, thus achieving high model generalization. We implemented our developed framework in a virtual testbed calibrated with measured data from Oak Ridge National Laboratory's Flexible Research Platform designed to mimic the operation of a typical small commercial building. The AFDD model is trained by the simulation data generated from the virtual testbed. The results show that (1) the developed framework improves the generalization of the AFDD model by 10.7% compared with literature-reported feature extraction and selection methods and (2) features with diverse window sizes and statistics are selected, providing insight into physical systems beyond the current understanding of buildings and faults and improving the detection and diagnostics of multiple fault types.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

A Tchebycheff-based multi-objective combined with a PSO–SQP dynamic real-time optimization framework for cycling energy systems

The aim in this work is to develop an optimization framework to address cycling of baseload energy systems due to the penetration of renewables into the grid. The developed strategy corresponds to a multi-objective and dynamic real-time optimization (MOO-DRTO) framework applied to a postcombustion MEA-based CO 2 capture process from a baseload coal-fired power plant under cycling conditions. A Tchebycheff-based method is used for the multi-objective optimization (MOO) component. Also, a hybrid approach consisting of Particle Swarm Optimization (PSO) and Sequential Quadratic Programming (SQP) is implemented for the first time in process systems engineering to solve the dynamic real-time optimization (DRTO) component. The objectives considered in the MOO-DRTO framework are economic and environmental. The proposed MOO-DRTO strategy is successfully implemented and 24-h optimal output trajectories for the carbon capture system under cycling are generated. Also, the optimal compromise is chosen from the Pareto front according to a set of selected weights for the objectives with minimal interaction between the framework and decision maker. The results indicated that the developed framework has potential to be extended to plant-wide optimization applications under cycling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

An artificial neural network framework for reduced order modeling of transient flows

Here, this paper proposes a supervised machine learning framework for the non-intrusive model order reduction of unsteady fluid flows to provide accurate predictions of non-stationary state variables when the control parameter values vary. Our approach utilizes a training process from full-order scale direct numerical simulation data projected on proper orthogonal decomposition (POD) modes to achieve an artificial neural network (ANN) model with reduced memory requirements. This data-driven ANN framework allows for a nonlinear time evolution of the modal coefficients without performing a Galerkin projection. Our POD-ANN framework can thus be considered an equation-free approach for latent space dynamics evolution of nonlinear transient systems and can be applied to a wide range of physical and engineering applications. Within this framework we introduce two architectures, namely sequential network (SN) and residual network (RN), to train the trajectory of modal coefficients. We perform a systematic analysis of the performance of the proposed reduced order modeling approaches on prediction of a nonlinear wave-propagation problem governed by the viscous Burgers equation, a simplified prototype setting for transient flows. We find that the POD-ANN-RN yields stable and accurate results for test problems assessed both within inside and outside of the database range and performs significantly better than the standard intrusive Galerkin projection model. Finally, our results show that the proposed framework provides a non-intrusive alternative to the evolution of transient physics in a POD basis spanned space, and can be used as a robust predictive model order reduction tool for nonlinear dynamical systems.

42 ENGINEERING↗
DOE OSTI2026

Inverse design of hypoeutectoid pearlite steel microstructures using a deep learning and genetic algorithm optimization framework

Goal-oriented microstructure design in metallic materials is a challenging task due to complex structure-property relationships. Traditional experimental and computational approaches are time-intensive and economically inefficient, limiting their applicability for large-scale design space exploration. Here, in this work, we propose an end-to-end framework that integrates deep learning models with genetic optimization to design microstructures with targeted mechanical properties. Deep learning models enable accurate forward design, while their integration with genetic optimization enables efficient inverse design within a few hours, compared to days or weeks using conventional finite element simulations. The framework combines experimental characterization and finite element modeling to analyze the influence of microstructural features on the mechanical behavior of hypoeutectoid steels. Data from both experiments and simulations are used to train the deep learning models. To demonstrate its effectiveness, we apply the framework to 0.63% carbon steel with proeutectoid ferrite and pearlite phases, commonly used in industrial applications. In this study, 2D microstructures were used for modeling, selected primarily for computational efficiency and to establish proof of concept. The framework successfully optimizes microstructures for targeted yield strength, ultimate strength, and stress concentration factors while significantly reducing computational time. Beyond hypoeutectoid steels, this scalable framework can be extended to other material systems and integrated with additive manufacturing, offering an efficient approach for accelerating microstructure design for specific engineering applications.

ConvLSTM↗
DOE OSTI2025

Enhanced MPM framework with multipatch isogeometric analysis for geotechnical applications

Achieving stable stress solutions at large strains using the Material Point Method (MPM) is challenging due to the accumulation of errors associated with geometry discretization, cell-crossing noise, and volumetric locking. Several simplified attempts exist in the literature to mitigate these errors, including higher-order frameworks. However, the stability of the MPM solution in such frameworks has been limited to simple geometries and the single-phase formulation (i.e., neglecting pore fluid). Although never explored, multipatch isogeometric analysis offers desirable qualities to simulate complex geometries while mitigating errors in the MPM. The degree of required high-order spatial integration has also never been investigated to infer a minimum limit for the stability of the stress solution in MPM. This paper presents a general-purpose numerical framework for simulating stable stresses in porous media, capturing both near incompressibility and multiphase interactions. First, the numerical framework is presented considering Non-Uniform Rational B-splines (NURBS) to perform isogeometric analysis (IGA) in MPM. Additionally, a volumetric strain smoothing algorithm is used to alleviate errors associated with volumetric locking. Second, the manifestation of cell-crossing errors is assessed via a series of problems with orders ranging from linear to cubic interpolation functions. Third, the use of NURBS is investigated and verified for problems with circular geometries. Finally, multipatch analysis is deployed to simulate plane strain and 3D penetration in soils, considering nearly incompressible elastoplastic (total stress) analysis and fully-coupled hydro-mechanical (effective stress) analysis. The stability of the solution is also analyzed for different constitutive models. From the results, it can be concluded that the framework using cubic interpolation functions with strain smoothing is the most convenient, presenting stable stress solutions for a broad range of multiphase geotechnical applications.

58 GEOSCIENCES↗
DOE OSTI2013

The impact and effectiveness of health impact assessment: A conceptual framework

The use of health impact assessment (HIA) has expanded rapidly and there are increasing demands for it to demonstrate its effectiveness. This paper presents a conceptual framework for evaluating HIA and describes its development through (i) a review of the literature, (ii) a review of work undertaken as part of a major HIA capacity building project and (iii) an in-depth study of seven completed HIAs. The framework emphasises context, process and impacts as key domains in understanding and evaluating the effectiveness of an HIA. This new framework builds upon the existing approaches to evaluating HIA and extends them to reflect the broad range of factors that comprise and influence the effectiveness of HIAs. It may be of use in evaluating completed HIAs and in planning HIAs that are yet to be undertaken. -- Highlights: ► The first empirically-derived conceptual framework for evaluating HIA ► It may also be useful for planning and reporting on HIAs. ► The framework emphasises context, process and impacts as key domains. ► A broad range of factors influence the effectiveness of HIAs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Framework for assessing impacts of pile-driving noise from offshore wind farm construction on a harbour seal population

Offshore wind farm developments may impact protected marine mammal populations, requiring appropriate assessment under the EU Habitats Directive. We describe a framework developed to assess population level impacts of disturbance from piling noise on a protected harbour seal population in the vicinity of proposed wind farm developments in NE Scotland. Spatial patterns of seal distribution and received noise levels are integrated with available data on the potential impacts of noise to predict how many individuals are displaced or experience auditory injury. Expert judgement is used to link these impacts to changes in vital rates and applied to population models that compare population changes under baseline and construction scenarios over a 25 year period. We use published data and hypothetical piling scenarios to illustrate how the assessment framework has been used to support environmental assessments, explore the sensitivity of the framework to key assumptions, and discuss its potential application to other populations of marine mammals. -- Highlights: • We develop a framework to support Appropriate Assessment for harbour seal populations. • We assessed potential impacts of wind farm construction noise. • Data on distribution of seals and noise were used to predict effects on individuals. • Expert judgement linked these impacts to vital rates to model population change. • We explore the sensitivity of the framework to key assumptions and uncertainties.

54 ENVIRONMENTAL SCIENCES↗