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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.

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At least 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

MBMS1.0: An Open-Source Code for Modeling and Simulation of Membrane-Based Dehumidification and Energy Recovery

Air dehumidification processes are important and significantly impact both the performance of building ventilation and air conditioning systems, and the health of occupants. In a membrane-based dehumidifier, a permselective membrane is adopted to separate the two flow streams at feed and permeate sides. The feed side is continuously supplied with humid air at atmospheric pressure, while the permeate side is connected to a vacuum pump to produce vacuum or a low permeate vapor pressure as a driving force for water vapor permeation. The software MBMS 1.0 enables modeling and simulation of the design and configuration optimization of a membrane-based air-to-air (A2A) or air-to-vapor (A2V) device. A first-order physical-constant model was developed to reasonably account for the fundamental heat and mass transfer processes involved.

Gao, Zhiming↗
DOE OSTI2020

OpenStudio System-level KPI Reporting Measure v1.0

This is a OpenStudio measure that calculates and reports the system-level key performance indicators (KPIs) for evaluating building energy performance at the system level. The systems are defined by the service it provides in commercial buildings, which include (1) lighting, (2) Miscellaneous Electric Loads (MELs), (3) Heating, Ventilation and Air Conditioning (HVAC), and (4) Service Water Heating (SWH).

Li, Han↗
DOE OSTI2015

Multi-period Nash bargaining for Coordination of Distributed Energy Resources

Flexibility from distributed energy resources presents an enormous potential to provide various services to the smart grid. In this paper, we propose a unified hierarchical framework for aggregation and coordination of various flexible loads, such as commercial building Heating, Ventilation, and Air-Conditioning (HVAC) systems, Thermostatically Controlled Loads (TCLs), Distributed Energy Storages (DESs), residential Pool Pumps (PPs), and Electric Vehicles (EVs). Moreover, a multistage Nash-bargaining-based control strategy is proposed to coordinate different aggregations of flexible loads for demand response. Case studies are provided to demonstrate the efficacy of our proposed framework and coordination strategy in managing peak power demand in a community.

Hao, He↗
DOE OSTI2021

Functional Mock-up Interface - Machine Learning Center (FMI-MLC) v1

The Functional Mock-up Interface - Machine Learning Center is a tool to interface the Python-Tensorflow library with building simulation models, to develop and train machine learning-based controls. In particular, this framework allows the use of reinforcement learning through the standardized Functional Mock-up Interface, an open industry standard for co-simulation. First application was the development of a controller for dynamic façade and heating ventilation and air conditioning (HVAC) systems.

Gehbauer, Christoph↗
DOE OSTI2021

Budget Constrained Machine Learning for Early Prediction of Adverse Outcomes for COVID-19 Patients

Background: Machine learning (ML) based risk stratification models of Electronic Health records (EHR) data may help to optimize treatment of COVID-19 patients, but are often limited by their lack of clinical interpretability and cost of laboratory tests. We develop a ML based tool for predicting adverse outcomes based on EHR data to optimize clinical utility under a given cost structure. This cohort study was performed using deidentified EHR data from COVID-19 patients from ProMedica Healthcare in northwest Ohio and southeastern Michigan. Methods: We tested performance of various ML approaches for predicting either increasing ventilatory support or mortality and the set of model features under a budget constraint was optimized via exhaustive search across all combinations of features. Results: The optimal sets of features for predicting ventilation under any budget constraint included demographics and comorbidities (DCM), basic metabolic panel (BMP), D-dimer, lactate dehydrogenase (LDH), erythrocyte sedimentation rate (ESR), CRP, brain natriuretic peptide (BNP), and procalcitonin and for mortality included DCM, BMP, complete blood count, D-dimer, LDH, CRP, BNP, procalcitonin and ferritin. Conclusions: This study presents a quick, accurate and cost-effective method to evaluate risk of deterioration for patients with SARS-CoV-2 infection at the time of clinical evaluation.

Cadena Pico, JoseE.↗
DOE OSTI2014

Facility Energy Decision System (FEDS) version 7.0

Designed for building energy managers, utilities and firms providing energy services, FEDS provides a comprehensive and user-friendly method for users to quickly and accurately identifying energy conversion and end-use technology improvements that offer maximum savings in energy usage and cost. FEDS enables the user to assess energy efficiency and consumption, identify retrofit opportunities, select minimum life cycle costs, determine payback, and prioritize investments in energy efficiency retrofit projects for multiple or single buildings across a particular site. As part of the life-cycle cost optimization it also considers several options for partial or complete abandonment of central energy plants including: individual technologies dropping off a thermal loop, a loop and all technologies dropping off a central plant, and all technologies and loops dropping off a central plant resulting in its complete abandonment. Improvements in release 7.0 include: FEDS 7.0 is now a full hourly simulation model (runs every hour of the year as opposed to the previous simplified hourly approach which ran 9 24-hour periods to represent each month). Enhanced building operation and occupancy modeling; New HVAC technology options (VAV, Economizers, Demand Controlled Ventilation, Terminal Reheat, Subcool Dehumidification); Additional chiller types; New lighting technologies (LED, Halogen, Induction, additional fluorescent options); Completely updated retrofit cost and performance data; Regional cost data tied to zip code (previously applied state level averages); Updated and enhanced reporting capabilities; and New pier floor model

Dirks, James↗
DOE OSTI2022

Haxall-based (Axon) fault auto-correction package for building HVAC system (Haxall-based Fault Correction) v1.0

Haxall-based Fault Correction is a set of fault auto-correction algorithms implemented using the Axon language. These algorithms can automatically fix equipment and control problems as they arise and improve the operation of building Heating, Ventilation, and Air Conditioning (HVAC) systems. The coded auto-correction algorithms include mitigation of rogue zones, ASHRAE Guideline 36 static pressure and supply air reset, resolution of control hunting due to improper settings in a proportional-integral-derivative controller, correction of biased temperature sensors, etc. FDD tools with enhanced auto-correction capability can resolve control problems as they are detected, increasing energy savings and emissions reductions while freeing up operational staff expertise for the hardest facility problems.

Vitti, Raphael↗
DOE OSTI2016

Image Processing Occupancy Sensor

The Image Processing Occupancy Sensor, or IPOS, is a novel sensor technology developed at the National Renewable Energy Laboratory (NREL). The sensor is based on low-cost embedded microprocessors widely used by the smartphone industry and leverages mature open-source computer vision software libraries. Compared to traditional passive infrared and ultrasonic-based motion sensors currently used for occupancy detection, IPOS has shown the potential for improved accuracy and a richer set of feedback signals for occupant-optimized lighting, daylighting, temperature setback, ventilation control, and other occupancy and location-based uses. Unlike traditional passive infrared (PIR) or ultrasonic occupancy sensors, which infer occupancy based only on motion, IPOS uses digital image-based analysis to detect and classify various aspects of occupancy, including the presence of occupants regardless of motion, their number, location, and activity levels of occupants, as well as the illuminance properties of the monitored space. The IPOS software leverages the recent availability of low-cost embedded computing platforms, computer vision software libraries, and camera elements.

Source record↗
DOE OSTI2019

VOLTTRON/econ-dispatch

Work space for in development Economic Dispatch Application. Multi-purpose open-source control algorithms that will ensure real-time optimal operation, increase electric grid reliability, and lead to the goal of clean, efficient, reliable and affordable next generation building-integrated combine cooling, heating and power (CHP) system.The CHP system could include conventional heating, ventilation, air conditioning (HVAC) systems, distributed generation (DG), local storage (both thermal and electric) and local solar photovoltaic (PV) systems.

Katipamula, Srinivas↗
DOE OSTI2023

Dynamic Subgrid Turbulence Modeling for Shallow Cumulus Convection Simulations beyond LES Resolutions

A scale-dependent dynamic Smagorinsky model is implemented in the Met Office/NERC Cloud (MONC) model using two averaging flavors, along Lagrangian pathlines and local moving averages. The dynamic approaches were compared against the conventional Smagorinsky–Lilly scheme in simulating the diurnal cycle of shallow cumulus convection. The simulations spanned from the LES to the near-gray-zone and gray-zone resolutions and revealed the adaptability of the dynamic model across the scales and different stability regimes. The dynamic model can produce a scale- and stability-dependent profile of the subfilter turbulence length scale across the chosen resolution range. At gray-zone resolutions the adaptive length scales can better represent the early precloud boundary layer leading to temperature and moisture profiles closer to the LES compared to the standard Smagorinsky. As a result, the initialization and general representation of the cloud field in the dynamic model is in good agreement with the LES. In contrast, the standard Smagorinsky produces a less well-mixed boundary layer, which fails to ventilate moisture from the boundary layer, resulting in the delayed spinup of the cloud layer. Moreover, strong downgradient diffusion controls the turbulent transport of scalars in the cloud layer. However, the dynamic approaches rely on the resolved field to account for nonlocal transports, leading to overenergetic structures when the boundary layer is fully developed and the Lagrangian model is used. Introducing the local averaging version of the model or adopting a new Lagrangian time scale provides stronger dissipation without significantly affecting model behavior.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Development of a simplified calibrated building simulation model of a supermarket for proposed ECMs and control strategies impact evaluation

Calibrated building energy simulation is an important pathway to more energy-efficient buildings, but the information requirements of some approaches to this problem are significant. This is particularly true for supermarkets and other so-called “big-box” retail stores. Another characteristic of supermarkets is the significant interaction between Heating Ventilating and Air Conditioning (HVAC) and refrigeration systems in these buildings. These buildings could contain a wide variety of systems and a degree of load diversity that makes calibrated modeling a challenge. This paper describes a simplified approach that uses OpenStudio and EnergyPlus to combine known building parameters with “typical” parameters, resulting in a simplified building that is amenable to calibration. This approach was applied to a big-box store located in Nashville, Tennessee, and a calibrated model was obtained that was used to study potential energy conservation measures. Further, the paper also explores the capabilities of whole-building energy modeling tools, such as EnergyPlus, for modeling the HVAC controls and sequences and their impact evaluation. Although some measures are precluded by the model simplicity, several measures were found to improve the efficiency of the model and demonstrate that the simplified modeling approach is effective. Practical Application: This paper introduces a hybrid approach of building energy model calibration using limited information available from the actual building in combination with characteristics of a “typical” building of the same type. This hybrid approach would also be applicable for other building types than discussed in this paper to calibrate the building energy model using limited information from the actual building.

42 ENGINEERING↗
DOE OSTI2024

Dialogue Between Lighting and HVAC Systems: Improving building system integration

Lighting systems have long been capable of sensing when someone enters or exits a room and using that knowledge to turn lights on or off. More recently, connected lighting systems with sensors integrated into every luminaire have become broadly available, facilitating highly granular occupancy detection. Similarly, HVAC systems have long been able to use an understanding of building occupancy to adjust temperature setpoints and reduce energy use without significant impacts to occupant comfort. Energy codes (e.g., ASHRAE/IES Standard 90.1, IECC, Title 24) now require “occupied standby HVAC control,” whereby systems adjust both temperature and ventilation setpoints in zones that are determined to be unoccupied during normal occupancy hours. Here, this article discusses current issues that stymie the integration of Lighting and HVAC systems, and DOE activities focused on addressing them.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Toward improved thermal exposure classes for structural firefighters

In the early 1970s, there was an initial effort to quantify the conditions under which firefighters are expected to perform. Harvey Utech led this endeavor by defining three levels of thermal exposure—routine, ordinary, and emergency—which were characterized by combining a range of air temperatures and radiative heat fluxes. In the last half-century, there has been a concerted scientific effort to further understand the conditions to which firefighters are exposed during structural firefighting. Research has been conducted on the resiliency of turnout gear and facepiece lenses, the thermal conditions observed during a structure fire, and the impact of firefighter tactics such as ventilation and suppression. The authors synthesize the results from these research areas to update the original thermal classifications to six categories of exposure—routine, Ordinary I, Ordinary II, Emergency I, Emergency II, and Emergency III—which are more representative of the operating environment and protective equipment thresholds that firefighters should be aware of during firefighting operations and tactical decision-making.

Weinschenk, Craig↗
DOE OSTI2023

Circulating SARS-CoV-2 + megakaryocytes are associated with severe viral infection in COVID-19

Several independent lines of evidence suggest that megakaryocytes are dysfunctional in severe COVID-19. Herein, we characterized peripheral circulating megakaryocytes in a large cohort of inpatients with COVID-19 and correlated the subpopulation frequencies with clinical outcomes. Using peripheral blood, we show that megakaryocytes are increased in the systemic circulation in COVID-19, and we identify and validate S100A8/A9 as a defining marker of megakaryocyte dysfunction. We further reveal a subpopulation of S100A8/A9 + megakaryocytes that contain severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) protein and RNA. Using flow cytometry of peripheral blood and in vitro studies on SARS-CoV-2–infected primary human megakaryocytes, we demonstrate that megakaryocytes can transfer viral antigens to emerging platelets. Mechanistically, we show that SARS-CoV-2–containing megakaryocytes are nuclear factor κB (NF-κB)-activated, via p65 and p52; express the NF-κB–mediated cytokines interleukin-6 (IL-6) and IL-1β; and display high surface expression of Toll-like receptor 2 (TLR2) and TLR4, canonical drivers of NF-κB. In a cohort of 218 inpatients with COVID-19, we correlate frequencies of megakaryocyte subpopulations with clinical outcomes and show that SARS-CoV-2–containing megakaryocytes are a strong risk factor for mortality and multiorgan injury, including respiratory failure, mechanical ventilation, acute kidney injury, thrombotic events, and intensive care unit admission. Furthermore, we show that SARS-CoV-2 + megakaryocytes are present in lung and brain autopsy tissues from deceased donors who had COVID-19. To our knowledge, this study offers the first evidence implicating SARS-CoV-2 + peripheral megakaryocytes in severe disease and suggests that circulating megakaryocytes warrant investigation in inflammatory disorders beyond COVID-19.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Diagnosis and management of inhalation injury: an updated review

In this article we review recent advances made in the pathophysiology, diagnosis, and treatment of inhalation injury. Historically, the diagnosis of inhalation injury has relied on nonspecific clinical exam findings and bronchoscopic evidence. The development of a grading system and the use of modalities such as chest computed tomography may allow for a more nuanced evaluation of inhalation injury and enhanced ability to prognosticate. Supportive respiratory care remains essential in managing inhalation injury. Adjuncts still lacking definitive evidence of efficacy include bronchodilators, mucolytic agents, inhaled anticoagulants, nonconventional ventilator modes, prone positioning, and extracorporeal membrane oxygenation. Recent research focusing on molecular mechanisms involved in inhalation injury has increased the number of potential therapies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

A Method to Estimate the Chronic Health Impact of Air Pollutants in U.S. Residences

Background: Indoor air pollutants (IAPs) cause multiple health impacts. Prioritizing mitigation options that differentially affect individual pollutants and comparing IAPs with other environmental health hazards require a common metric of harm. Objectives: Our objective was to demonstrate a methodology to quantify and compare health impacts from IAPs. The methodology is needed to assess population health impacts of large-scale initiatives—including energy efficiency upgrades and ventilation standards—that affect indoor air quality (IAQ). Methods: Available disease incidence and disease impact models for specific pollutant–disease combinations were synthesized with data on measured concentrations to estimate the chronic heath impact, in disability-adjusted life-years (DALYs) lost, due to inhalation of a subset of IAPs in U.S. residences. Model results were compared with independent estimates of DALYs lost due to disease. Results: Particulate matter ≤ 2.5 μm in aerodynamic diameter (PM2.5), acrolein, and formaldehyde accounted for the vast majority of DALY losses caused by IAPs considered in this analysis, with impacts on par or greater than estimates for secondhand tobacco smoke and radon. Confidence intervals of DALYs lost derived from epidemiology-based response functions are tighter than those derived from toxicology-based, interspecies extrapolations. Statistics on disease incidence in the United States indicate that the upper-bound confidence interval for aggregate IAP harm is implausibly high. Conclusions: The approach demonstrated in this study may be used to assess regional and national initiatives that affect IAQ at the population level. Cumulative health impacts from inhalation in U.S. residences of the IAPs assessed in this study are estimated at 400–1,100 DALYs lost annually per 100,000 persons.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Proposal for secondary enclosure setup for experiments to expose plasma facing materials to tritiated plasma in VISIONI

VISIONI is an equipment at SCK-CEN that allows the exposure of candidate plasma facing materials to tritium - deuterium plasmas at ITER first wall conditions. VISIONI itself, being a vacuum setup, acts as primary confinement. To protect operators against exposure to a tritiated atmosphere VISIONI must be placed in a secondary confinement. The current Tritium lab at SCK-CEN has a walk-in process cell which can be used to enclose the plasma chamber and diagnostics of the VISIONI setup, which have a limited tritium inventory. This allows easy accessibility to the setup in a well-ventilated environment. Routine operations should be conducted from outside the process cell and maintenance operations can be conducted from within the process cell with proper protections. The tritium storage and supply can be enclosed in a glove box with a dedicated air detritiation system which is activated during an experiment or in case of an incident. The detritiation system will oxidize tritium and capture it on molecular sieves. By using this confinement approach it is possible to expose materials to a tritiated plasma while maintaining good accessibility of the VISIONI setup. This paper describes the proposed confinement system and compares it to the most common approach where the entire system is enclosed into one large glovebox.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Analysis of activated air following high yield shots in the NIF

During the ignition experimental campaign, the National Ignition Facility (NIF) is expected to perform shots with varying fusion yield (up to 20 MJ or 7.1 x 10 18 neutrons per shot) and a maximum annual yield of 1200 MJ. A detailed MCNP model of the Target Bay (TB) and the two switchyards (SY) has been developed to estimate the post-shot radiation environment inside the facility. During D-T shots, a pulse of 14.1 MeV neutrons streaming outside the Target Chamber (TC) will activate the air present inside the TB and the argon gas inside the laser tubes. Smaller levels of activity are also generated in the SY air and in the argon portion of the SY laser beam path. The activated TB air will be mixed with fresh air from the Operations Support Building (OSB) before release through the stack. Flow of activated air from the Target Bay is controlled by the heating, ventilating, and air conditioning (HVAC) system. 16 N (T 1/2 = 7.13 s) dominates the radiation levels during the first minute following the shot. It is expected that 16 N will decay away during the confinement time before releasing the TB air through the stack. The other major contributors are 13 N (T 1/2 = 9.97 min) and 41 Ar (T 1/2 = 1.83 h). In general a low dose rate of < 1 μSv/h is expected near the stack during the first few hours following a 20 MJ shot. Here, the amount of activated Target Bay air released through the stack is very small and does not pose significant hazard to personnel or the environment. In the mean time, due to a very small leakage rate out of the laser tubes, the activated argon gas decays within the tubes and any resulting release to the environment is insignificant.

61 RADIATION PROTECTION AND DOSIMETRY↗