Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Framework”

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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

The Iterative Processing Framework: A New Paradigm for Automatic Event Building

Abstract In a traditional data-processing pipeline, waveforms are acquired, a detector makes the signal detections (i.e., arrival times, slownesses, and azimuths) and passes them to an associator. The associator then links the detections to the fitting-event hypotheses to generate an event bulletin. Most of the time, this traditional pipeline requires substantial human-analyst involvement to improve the quality of the resulting event bulletin. For the year 2017, for instance, International Data Center (IDC) analysts rejected about 40% of the events in the automatic bulletin and manually built 30% of the legitimate events. Here, we introduce an iterative processing framework (IPF) that includes a new data-processing module that incorporates automatic analyst behaviors (auto analyst [AA]) into the event-building pipeline. In the proposed framework, through an iterative process, the AA takes over many of the tasks traditionally performed by human analysts. These tasks can be grouped into two major processes: (1) evaluating small events with a low number of location-defining arrival phases to improve their formation; and (2) scanning for and exploiting unassociated arrivals to form potential events missed by previous association runs. To test the proposed framework, we processed a two-week period (15–28 May 2010) of the signal-detections dataset from the IDC. Comparison with an expert analyst-reviewed bulletin for the same time period suggests that IPF performs better than the traditional pipelines (IDC and baseline pipelines). The majority of the additional events built by the AA are low-magnitude events that were missed by these traditional pipelines. The AA also adds additional signal detections to existing events, which saves analyst time, even if the event locations are not significantly affected.

58 GEOSCIENCES↗
DOE OSTI2020

Open-Source Framework for Data Storage and Visualization of Real-Time Experiments

Digital real time simulators (DRTS) are increasingly being used for the evaluation of power hardware and controller hardware in the laboratory prior to field deployment. Although DRTS are capable of simulating large models in real-time, it is challenging to visualize the results of large models without overdrawing or confounding the viewer. This paper provides an open-source framework for users to visualize their DRTS-based hardware-in-the-loop (HIL) experimental results in real-time. This proposed framework can be used by experimental test beds that can push data through an internet protocol based network. The proposed framework includes three main components. First, it includes the DRTS that generates and pushes the data to a relay. Second, it includes an application that serves multiple purposes, from data storage, testing, and translation of the data to a publisher/subscriber protocol. Finally, it includes libraries and applications that can be used to visualize the data by subscribing to the relay. This framework is available in open source, and it is tested using the HIL platform developed for testing advanced distribution management systems.

advanced distribution management systems↗
DOE OSTI2021

Siloxyaluminate and Siloxygallate Complexes as Models for Framework and Partially Hydrolyzed Framework Sites in Zeolites and Zeotypes.

Anionic molecular models for nonhydrolyzed and partially hydrolyzed aluminum and gallium framework sites on silica, M[OSi(OtBu) 3 ] 4 - and HOM[OSi(OtBu) 3 ] 3 - (where M=Al or Ga), were synthesized from anionic chlorides Li{M[OSi(OtBu) 3 ] 3 Cl} in salt metathesis reactions. Sequestration of lithium cations with [12]crown-4 afforded charge-separated ion pairs composed of monomeric anions M[OSi(OtBu) 3 ] 4 - with outer-sphere [([12]crown-4) 2 Li] + cations, and hydroxides {HOM[OSi(OtBu) 3 ] 3 } with pendant [([12]crown-4)Li] + cations. These molecular models were characterized by single-crystal X-ray diffraction, vibrational spectroscopy, mass spectrometry and NMR spectroscopy. Upon treatment of monomeric [([12]crown-4)Li]{HOM[OSi(OtBu) 3 ] 3 } complexes with benzyl alcohol, benzyloxide complexes were formed, modeling a possible pathway for the formation of active sites for Meerwin-Ponndorf-Verley (MPV) transfer hydrogenations with Al/Ga-doped silica catalysts.

Dombrowski, James P↗
DOE OSTI2019

A self-correcting variable-metric algorithm framework for nonsmooth optimization

Abstract An algorithm framework is proposed for minimizing nonsmooth functions. The framework is variable metric in that, in each iteration, a step is computed using a symmetric positive-definite matrix whose value is updated as in a quasi-Newton scheme. However, unlike previously proposed variable-metric algorithms for minimizing nonsmooth functions, the framework exploits self-correcting properties made possible through Broyden–Fletcher–Goldfarb–Shanno-type updating. In so doing, the framework does not overly restrict the manner in which the step computation matrices are updated, yet the scheme is controlled well enough that global convergence guarantees can be established. The results of numerical experiments for a few algorithms are presented to demonstrate the self-correcting behaviours that are guaranteed by the framework.

Mathematics↗
DOE OSTI2023

Meld: Exploring the Feasibility of a Framework-less Framework

HEP data-processing frameworks are essential ingredients in getting from raw data to physics results. But they are often tricky to use well, and they present a significant learning barrier for the beginning HEP physicist. In addition, existing frameworks typically support rigid, collider-based data models, which do not map well to neutrino-physics experiments like DUNE. Neutrino physicists thus expend significant effort working around framework limitations instead of using a framework that directly supports their needs. Presented here is Meld, a Fermilab R&D project, which intends to address these limitations. By leveraging modern C++ capabilities, state-of-the-art concurrency libraries, and a flexible data model, it is possible for beginning (and seasoned) HEP physicists to execute framework programs easily and efficiently, with minimal coupling to framework-specific constructs. Meld aims to directly support the frameworks needs of neutrino experiments like DUNE as well as the more common collider-based experiments.

Knoepfel, Kyle J.↗
DOE OSTI2018

Record High Hydrogen Storage Capacity in the Metal–Organic Framework Ni 2 ( m -dobdc) at Near-Ambient Temperatures

Hydrogen holds promise as a clean alternative automobile fuel, but its on-board storage presents significant challenges due to the low temperatures and/or high pressures required to achieve a sufficient energy density. The opportunity to significantly reduce the required pressure for high density H 2 storage persists for metal-organic frameworks due to their modular structures and large internal surface areas. The measurement of H 2 adsorption in such materials under conditions most relevant to on-board storage is crucial to understanding how these materials would perform in actual applications, although such data have to date been lacking. In the present work, the metal-organic frameworks M 2 (m-dobdc) (M = Co, Ni; m-dobdc 4- = 4,6-dioxido-1,3-benzenedicarboxylate) and the isomeric frameworks M 2 (dobdc) (M = Co, Ni; dobdc 4- = 1,4-dioxido-1,3-benzenedicarboxylate), which are known to have open metal cation sites that strongly interact with H 2 , were evaluated for their usable volumetric H 2 storage capacities over a range of near-ambient temperatures relevant to on-board storage. Based upon adsorption isotherm data, Ni 2 (m-dobdc) was found to be the top-performing physisorptive storage material with a usable volumetric capacity between 100 and 5 bar of 11.0 g/L at 25 °C and 23.0 g/L with a temperature swing between -75 and 25 °C. Additional neutron diffraction and infrared spectroscopy experiments performed with in situ dosing of D 2 or H 2 were used to probe the hydrogen storage properties of these materials under the relevant conditions. Finally, the results provide benchmark characteristics for comparison with future attempts to achieve improved adsorbents for mobile hydrogen storage applications.

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

Functionalized Porous Aromatic Frameworks as High‐Performance Adsorbents for the Rapid Removal of Boric Acid from Water

Abstract This study demonstrates that functionalized, highly porous polymers are promising for the adsorptive capture of boric acid, a neutral contaminant that is difficult to remove from seawater using conventional reverse osmosis membranes. Appending N ‐methyl‐d‐glucamine (NMDG) to the pore walls of high‐surface‐area porous aromatic frameworks (PAFs) yields the adsorbents PAF‐1‐NMDG and P2‐NMDG in a simple two‐step synthesis. The boron‐selective PAFs demonstrate adsorption capacities that are up to 70% higher than those of a commercial boron‐selective resin, Amberlite IRA743, and markedly faster adsorption rates, owing to their higher NMDG loadings and greater porosities relative to the resin. Remarkably, PAF‐1‐NMDG is able to reduce the boron concentration in synthetic seawater from 2.91 to <0.5 ppm in less than 3 min at an adsorbent loading of only 0.3 mg mL −1 . The boron adsorption rate constants of both frameworks, determined via a pseudo‐second‐order rate model, represent the highest values reported in the literature—in most cases orders of magnitude higher than those of other boron‐selective adsorbents. The frameworks can also be readily regenerated via mild acid/base treatment and maintain constant boron adsorption capacities for at least 10 regeneration cycles. These results highlight the numerous advantages of PAFs over traditional porous polymers in water treatment applications.

Kamcev, Jovan↗
DOE OSTI2021

A holistic framework integrating plant-microbe-mineral regulation of soil bioavailable nitrogen

Abstract Soil organic nitrogen (N) is a critical resource for plants and microbes, but the processes that govern its cycle are not well-described. To promote a holistic understanding of soil N dynamics, we need an integrated model that links soil organic matter (SOM) cycling to bioavailable N in both unmanaged and managed landscapes, including agroecosystems. We present a framework that unifies recent conceptual advances in our understanding of three critical steps in bioavailable N cycling: organic N (ON) depolymerization and solubilization; bioavailable N sorption and desorption on mineral surfaces; and microbial ON turnover including assimilation, mineralization, and the recycling of microbial products. Consideration of the balance between these processes provides insight into the sources, sinks, and flux rates of bioavailable N. By accounting for interactions among the biological, physical, and chemical controls over ON and its availability to plants and microbes, our conceptual model unifies complex mechanisms of ON transformation in a concrete conceptual framework that is amenable to experimental testing and translates into ideas for new management practices. This framework will allow researchers and practitioners to use common measurements of particulate organic matter (POM) and mineral-associated organic matter (MAOM) to design strategic organic N-cycle interventions that optimize ecosystem productivity and minimize environmental N loss.

Environmental Sciences & Ecology↗
DOE OSTI2021

A Flexible and Generic Functional Mock-up Unit Based Threat Injection Framework for Grid-interactive Efficient Buildings: A Case Study in Modelica

Grid-interactive efficient buildings (GEBs) have been considered as an important asset to support the power grid reliability by utilizing the demand flexibility offered by GEBs. GEBs are enabled by advances in sensors and controls, and the communication between building equipment, whole buildings, and the grid. The integration of different building technologies and network-based communication system makes GEBs vulnerable to passive threats such as equipment failure and active threats such as cyber-attacks. Modeling and simulation is an effective way to evaluate the impact of threats on the system performance. This paper proposes a generic and flexible threat injection framework for commonly-used building energy simulators such as EnergyPlus and Modelica to support threat modeling and evaluation. This framework leverages functional mock-up unit (FMU) to develop a general modeling interface for threat injection and simulation. A numerical case study using Modelica as a building energy simulator is conducted to demonstrate the capability of the framework for supporting single/multiple-order threat modeling and simulation of a GEB. Four threats and their combinations are injected on a Modelica-based threat-free building energy and control system, including operating supply fan at its full speed, remotely cycling the chiller on and off, blocking the chiller from receiving the chilled water supply temperature setpoints, and hijacking the global zone air temperature setpoint. Simulation results show that the cyber-attack that leads to short-term signal blocking has small effects on the system operation due to the "self-healing" feature of the heating, ventilation, and air-conditioning (HVAC) interactive control system. The threat that takes control of resetting the global zone air temperature setpoints has the most adverse impact on the system energy use, peak power demand, thermal comfort and the provision of demand flexibility. The combination of four threats have aggregative effects on the system but the effects are less than the additive effects of the individual threat.

Fu, Yanyang↗
DOE OSTI2019

A Highly Efficient Control Framework for Centralized Residential Charging Coordination of Large Electric Vehicle Populations

The potential for widespread adoption of plug-in electric vehicles (PEVs) brings with it the potential for negative impacts on the electric grid from electric vehicle charging. Uncoordinated PEV charging may increase electricity demand during peak hours, which could create concerns for the grid as the number of PEVs increases. Therefore, it is important to coordinate charging to alleviate potential negative impacts. Centralized charging coordination is preferred by grid operator over distributed control strategies because it can systematically allocate energy across a large population of PEVs and achieve global coordination benefits. However, centralized methods presented in the literature to date require prohibitively expensive computational resources and lack realistic PEV charging models. As a result, they cannot achieve the efficiency and accuracy required to implement charging coordination in the real world. This paper introduces a highly efficient receding horizon control framework that enables dynamic charging coordination for large PEV populations. A two-stage hierarchical optimization routine is proposed that aggregates individual PEV charging flexibility to reduce the computational complexity of the optimization process. The control framework is based on high-fidelity, validated charging system models and charging behavior models derived from a real-world data set of residential charging activities collected from thousands of charging stations over multiple years. Case studies illustrate that the proposed charging control framework is capable of effectively coordinating the charging of millions of PEVs using a standard desktop computer.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2019

Buckling of Two-Dimensional Covalent Organic Frameworks under Thermal Stress

Two-dimensional covalent organic frameworks (2D COFs) are periodic, permanently porous, and lightweight solids that are polymerized from topologically designed monomers. The predictable design and structural modularity of these materials make them promising candidates for applications including catalysis, environmental remediation, chemical separations, and organic electronics, many of which will require stability to mechanical and thermal stress. Based on their reinforced structures and high degradation temperatures, as determined by thermal gravimetric analysis (TGA), many reports have claimed that COFs have excellent thermal stability. However, their stability to heat and pressure has not been probed using methods that report on structural changes rather than the loss of volatile compounds. Here, we explore two structurally analogous 2D COFs with different polymerization chemistries using in operando X-ray diffraction (XRD), which demonstrates the loss of crystallinity at lower temperatures than the degradation temperatures measured by TGA. Density functional theory calculations suggest that an asymmetric buckling of the COF lattice is responsible for the observed loss of crystallinity. In addition to their thermal stability, XRD of the 2D COFs under gas pressures up to 100 bar showed no loss in crystallinity or structural changes, indicating that these materials are robust to mechanical stress by applied pressure. We expect that these results will encourage further exploration of COF stability as a function of framework design and isolated form, which will guide the design of frameworks that withstand demanding application-relevant conditions.

Evans, Austin↗
DOE OSTI2018

Charge Delocalization and Bulk Electronic Conductivity in the Mixed-Valence Metal–Organic Framework Fe(1,2,3-triazolate) 2 (BF 4 ) x

Metal–organic frameworks are of interest for use in a variety of electrochemical and electronic applications, although a detailed understanding of their charge transport behavior, which is of critical importance for enhancing electronic conductivities, remains limited. Herein, we report isolation of the mixed-valence framework materials, Fe(tri) 2 (BF 4 ) x (tri – = 1,2,3-triazolate; x = 0.09, 0.22, and 0.33), obtained from the stoichiometric chemical oxidation of the poorly-conductive iron(II) framework Fe(tri) 2 , and find that the conductivity increases dramatically with iron oxidation level. Notably, the most oxidized variant, Fe(tri) 2 (BF 4 ) 0.33 , displays a room-temperature conductivity of 0.3(1) S/cm, which represents an increase of eight orders of magnitude from that of the parent material and is one of the highest conductivity values reported among three-dimensional metal–organic frameworks. Detailed characterization of Fe(tri) 2 and the Fe(tri) 2 (BF 4 ) x materials via powder X-ray diffraction, Mössbauer spectroscopy, and IR and UV-vis-NIR diffuse reflectance spectroscopies reveals that the high conductivity arises from intervalence charge transfer between mixed-valence low-spin Fe II/III centers. Further, Mössbauer spectroscopy indicates the presence of a valence-delocalized Fe II/III species in Fe(tri) 2 (BF 4 ) x at 290 K, one of the first such observations for a metal–organic framework. The electronic structure of valence-pure Fe(tri) 2 and the charge transport mechanism and electronic structure of mixed-valence Fe(tri) 2 (BF 4 ) x frameworks are discussed in detail.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Colloidal Three-Dimensional Covalent Organic Frameworks and Their Application as Porous Liquids

Developing solid porous materials into free-flowing liquids with permanent porosity is a promising strategy for overcoming certain limitations of conventional sorbent materials employed in gas storage and separation applications. The ability to control the pore size and chemical functionalities of organic frameworks gives these particular nanoporous materials distinct advantages over other small cage-like molecules or hollow particles that have been developed into porous liquids. Here, we describe the synthesis of a 3D imine-linked colloidal covalent organic framework (COF)-based porous liquid, designed for efficient size-exclusion of solvent, as well as for long-term stability. By tethering ionic liquids to the colloid surface, the colloids can be dried, purified, and resuspended in a variety of solvents without irreversible aggregation typically observed of COF colloids. Colloid size could be controlled between 50 and 400 nm, with surface areas as high as 800 m2/g. The 3D intertwining morphology of the colloids had pore sizes ranging from 5 to 14 Å, allowing them to efficiently sizeexclude bulky ionic liquids. The COF colloids were stable towards flocculation in an ionic liquid for > 1 year. Permanent porosity was confirmed with a combination of 19F NMR measurements and gas sorption techniques. CO2 and CH4 uptake in these porous liquids increased more than 10 and 20-fold, respectively, over non-porous, neat ionic liquid control samples. The work not only advances the state of COF-based colloid science but also represents a practical advance towards developing more robust, tunable framework-based porous liquid materials for a host of gas storage and separation applications.

Mow, Rachel E.↗
DOE OSTI2021

Integrated Framework of Vehicle Dynamics, Instabilities, Energy Models, and Sparse Flow Smoothing Controllers

This work presents an integrated framework of: vehicle dynamics models, with a particular attention to instabilities and traffic waves; vehicle energy models, with particular attention to accurate energy values for strongly unsteady driving profiles; and sparse Lagrangian controls via automated vehicles, with a focus on controls that can be executed via existing technology such as adaptive cruise control systems. This framework serves as a key building block in developing control strategies for human-in-the-loop traffic flow smoothing on real highways. In this contribution, we outline the fundamental merits of integrating vehicle dynamics and energy modeling into a single framework, and we demonstrate the energy impact of sparse flow smoothing controllers via simulation results.

Lee, Jonathan W.↗
DOE OSTI2022

PowerGridworld: A Framework for Multi-Agent Reinforcement Learning in Power Systems: Preprint

We present the PowerGridworld software package to provide users with a light-weight, modular, and customizable framework for creating power systems-focused, multi-agent gym environments that readily integrate with existing training frameworks for reinforcement learning (RL). While many frameworks exist for training multi-agent (MA) RL policies, none exist to rapidly prototype and develop the environments themselves, especially in the context of heterogeneous (composite, multi-device) power systems where power flow solutions are required to define grid-level variables and costs. PowerGridworld is an open-source software package that helps to fill this gap. To highlight PowerGridworld's key features, we present two case studies and demonstrate learning multi-agent RL policies using both OpenAI's MADDPG and RLLib's PPO algorithms where, in both cases, at least some subset of agents incorporate elements of the power flow solution at each time step as part of their reward (negative cost) structures.

MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Digital twin framework for PIP-II linac: AI-driven multi-scale modeling from ion source to 800 MeV

The PIP-II superconducting linac at Fermilab is designed to deliver multi-megawatt proton beams for neutrino physics and other high-intensity applications. To expedite commissioning and enhance operational reliability, we have developed an EPICS-based data flow framework that seamlessly integrates digital twins (DT) with physical twins (PT). These digital twins comprise high-fidelity beam dynamics models or data-driven surrogate models connected to their physical counterparts through real-time diagnostics and advanced machine-learning algorithms.Central to this framework is Linac_Gen, an accelerated simulation tool that incorporates convolutional neural networks, random forests, and genetic algorithms to provide up to a tenfold speedup in optimizing the accelerator geometry model. An EPICS translator layer ensures interoperability by efficiently mapping lattice parameters across diverse simulation platforms.Our EPICS-based framework supports multiple operational modes—monitoring, passive learning, closed-loop control, and online learning—covering the entire machine lifecycle. By leveraging HPC resources and multi-objective optimization techniques, the digital twin enables adaptive trajectory correction, real-time fault detection, and predictive modeling of beam stability. This comprehensive approach paves the way for robust, high-intensity operation and data-driven accelerator R&D at Fermilab.

Pathak, Abhishek [Fermilab]↗