Solar simulation studies Summary
Solar simulation - paint testing, planning for high altitude tests of spectral irradiance, pressure arc and vortex stabilized radiation systems, and thermal control coating tests
SOLAR SIMULATION↗
SEARCH · Engineering Papers
Results for “emission control”
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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Photonic Refrigeration from Time-Modulated Thermal Emission
We develop theoretical and computational formalisms to describe thermal radiation from temporally modulated systems. We demonstrate that such a modulation results in a photon-based active cooling mechanism. This mechanism has a high thermodynamic performance that can approach the Carnot limit. Our work points to exciting new avenues in active, time-modulated control of thermal emission for cooling and energy harvesting applications.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Aerosol emissions from water-lean solvents for post-combustion CO 2 capture
Advanced water-lean solvents (WLS) for post-combustion CO 2 capture have been gaining interest due to their ability to reduce the parasitic penalty from energy needed for solvent regeneration. Commercial implementation of these novel CO 2 capture technologies hinges on successful control of amine emissions. RTI conducted a parametric study of fundamental and operational variables influence on overall amine aerosol and vapor emissions from our water-lean solvent eCO 2 Sol™ using our 6-kW equivalent bench-scale gas absorption system. The parametric testing used a simulated flue gas with 15 % CO 2 , 2.3–4.2 % H 2 O, and 0–6 ppm sulfite (SO 3 ) to examine the impact of the presence of aerosols to the capture performance and amine emissions from the system. The SO 3 reacts with water in the flue gas to create H 2 SO 4 , which forms liquid aerosol droplets and provide nucleation sites for growth of aerosols. Scanning Mobility Particle Sizer and Aerodynamic Particle Sizer instruments monitored the aerosol particle size distribution. Parametric testing results suggested that the presence of the aerosols in the flue gas could increase the overall amine emissions by 10X compared to the baseline emissions from WLS’s vapor pressure. Principal component analysis (PCA) and projection to latent squares (PLS) developed models to predict the aerosol-based amine emissions from process data. The predictive PLS model had a correlation coefficient (Q 2 ) of 0.92 and could predict the aerosol-based emissions from the NAS process with ±15 % accuracy (average absolute deviation, AAD). The PLS regression model also identified key variables affecting aerosol-based emissions from WLS.
42 ENGINEERING↗
Spectral albedo and emissivity of CO2 in Martian polar caps - Model results
In this paper, a snow albedo model previously developed for terrestrial snow is extended to the case of CO2 snow on Mars. Pure CO2 snow is calculated to have high albedo at visible wavelengths but not as high as that of water snow. At any given wavelength, the primary variable controlling albedo and emissivity is the snow grain size, with albedo decreasing and emissivity increasing as grain size increases. Observations that red albedo is much higher than blue albedo in the Martian south polar cap indicates that the snow or the atmosphere is contaminated with red dust. The absorption coefficient of CO2 ice in the thermal infrared is two to three orders of magnitude smaller than that measured for H2O ice. CO2 snow emissivity is therefore much lower than H2O snow, varying substantially with wavelength and quite sensitive to grain size and emission angle. Factors tending to increase emissivity are large grain size, small emission angle, and large concentrations of dust or water.
Warren, Stephen G.↗
Deep Reinforcement Learning Based Smart Water Heater Control for Reducing Electricity Consumption and Carbon Emission
Water heating is the third largest electricity consumer in U.S. households, after space heating and cooling. Thus, water heaters represent a significant potential for reducing electricity consumption and associated CO2 emissions of residential buildings. To this end, this study proposes a model-free deep reinforcement learning (RL) approach that aims to minimize the electricity consumption and the CO2 emissions of a heat pump water heater without affecting user comfort. In this approach, a set of RL agents focusing on either electricity saving or emission reduction, with different look ahead periods, were trained using the deep Q-networks (DQN) algorithm and their performance was tested on different hot water usage and Marginal Operating Emissions Rate (MOER) profiles. The testing results showed that the RL agents that focus on electricity saving can save electricity in the range of 12–22% by operating the water heater with maximum heat pump efficiency and minimum electric element utilization. On the other hand, the RL agents that focus on emission reduction reduced emissions in the range of 18–37% by making use of the variable MOER values. These RL agents used the heat pump and/or an element when the MOER values are low due to the availability of renewable energy sources (e.g., solar and wind) and mostly avoided the periods of carbon-intensive periods. Overall, these results showed that the proposed RL approach can help minimize the electricity consumption and the CO2 emissions of a heat pump water heater without having any prior knowledge about the device.
Amasyali, Kadir↗
Soil moisture controls over carbon sequestration and greenhouse gas emissions: a review
Not Available
54 ENVIRONMENTAL SCIENCES↗
A search for geographic control on the occurrence of magnetospheric ELF emissions
Search coil magnetometer data obtained in the magnetosphere on Ogo 5 and Ogo 6 were studied for evidence of man-induced stimulation of the two dominant electromagnetic emissions, chorus and plasmaspheric hiss. Variability of chorus with geographic longitude and enhancements, onsets, and quantum jumps in chorus emissions at frequencies related to harmonics of the earth's transmission lines are discussed. The enhancement of weak emissions in the 340-360 deg dipole longitude region during quiet geomagnetic conditions is present only when ELF hiss is weak, and will not contribute to the non-adiabatic dynamics of radiation belt electrons. It is concluded that the data analyzed is consistent with a predominantly natural origin for chorus and plasmaspheric hiss, and that triggered waves do not play a major role in the non-adiabatic dynamics of geomagnetically trapped electrons.
Tsurutani, B. T.↗
Seamlessly Fuel Flexible Heat Pump with Optimal Model-based Control Strategies to Reduce Peak Demand, Utility Cost and CO2 Emission
This research develops a novel hybrid fuel heat pump system for space heating of residential and small commercial buildings with built-in optimization and control. Whereas conventional dual fuel systems either run on gas or electricity at any given moment, the proposed seamlessly fuel flexible heat pump (SFFHP) simultaneously consumes gas and electricity and continuously optimizes the proportion of each. The building air flows across the heat pump condenser first and then flows across the furnace coil, and this reduces the heat pump temperature lift. The SFFHP delivers energy savings by allowing each subsystem (gas furnace and electric heat pump) to operate where it performs best to improve energy efficiency, minimize energy cost, and minimize carbon footprint. The capacities of the electric heat pump and gas furnace are continuously adjusted based on ambient conditions, utility price signals, and marginal grid emission signals. An optimal model predictive control strategy was developed with the goal of minimizing utility cost and minimizing CO2 emission. Two case studies were conducted to simulate the performance of SFFHP during the heating season in Chicago and Los Angeles, respectively. Compared with a conventional electric heat pump, SFFHP yields 33% utility cost reduction and 49% CO2 emission reduction in Chicago. Similarly, it achieves 23% utility cost reduction and 17% CO2 emission reduction in Los Angeles. Case studies demonstrate that SFFHP can deliver significant reductions in peak demand, utility cost, and CO2 emission. Due to the hybrid fuel nature of this novel equipment, user comfort will always be maintained. The fuel flexibility makes it an attractive option for demand response programs.
Li, Zhenning↗
Experimental clean combustor program: Diesel no. 2 fuel addendum, phase 3
A CF6-50 engine equipped with an advanced, low emission, double annular combustor was operated 4.8 hours with No. 2 diesel fuel. Fourteen steady-state operating conditions ranging from idle to full power were investigated. Engine/combustor performance and exhaust emissions were obtained and compared to JF-5 fueled test results. With one exception, fuel effects were very small and in agreement with previously obtained combustor test rig results. At high power operating condition, the two fuels produced virtually the same peak metal temperatures and exhaust emission levels. At low power operating conditions, where only the pilot stage was fueled, smoke levels tended to be significantly higher with No. 2 diesel fuel. Additional development of this combustor concept is needed in the areas of exit temperature distribution, engine fuel control, and exhaust emission levels before it can be considered for production engine use.
Gleason, C. C.↗
Performance of Continuous Emission Monitoring Solutions under a Single-Blind Controlled Testing Protocol
Not Available
54 ENVIRONMENTAL SCIENCES↗
Desert Dust, Industrialization and Agricultural Fires: Health Impacts of Outdoor Air Pollution in Africa
The African continent continuously experiences extreme aerosol load conditions, during which the World Health Organizational (WHO) clean air standard of 10 μgm(exp ‐3) of PM(2.5) mass is systematically exceeded. Africa holds the world largest source of desert dust emissions, undergoes strong industrial growth, and produces approximately a third of the Earth's biomass burning aerosol particles. Sub‐Saharan biomass burning is driven by agricultural practices, such as burning fields and bushes in the post‐harvest season for fertilization, land management and pest control. Thus, these emissions are predominantly anthropogenic. Here we use global atmospheric composition, climate, and health models to simulate the chemical composition of the atmosphere and calculate the mortality rates for Africa by distinguishing between purely natural, industrial/domestic and biomass burning emissions. Air quality related deaths in Africa rank within the top leading causes of death in Africa. Our results of ~780,000 premature deaths annually point to the extensive health impacts of natural emissions, high mortality rate caused by industrialization in Nigeria and South Africa, and to a smaller extent by fire emissions in Central and West Africa. 43,000 premature deaths in Africa are linked to biomass burning mainly driven by agriculture. Our results also show that natural sources, in particular windblown dust emissions, have large impacts on air quality and human health in Africa.
fires↗
Southeast Atmosphere Studies: Learning from Model-Observation Syntheses
Concentrations of atmospheric trace species in the United States have changed dramatically over the past several decades in response to pollution control strategies, shifts in domestic energy policy and economics, and economic development (and resulting emission changes) elsewhere in the world. Reliable projections of the future atmosphere require models to not only accurately describe current atmospheric concentrations, but to do so by representing chemical, physical and biological processes with conceptual and quantitative fidelity. Only through incorporation of the processes controlling emissions and chemical mechanisms that represent the key transformations among reactive molecules can models reliably project the impacts of future policy, energy and climate scenarios. Efforts to properly identify and implement the fundamental and controlling mechanisms in atmospheric models benefit from intensive observation periods, during which collocated measurements of diverse, speciated chemicals in both the gas and condensed phases are obtained. The Southeast Atmosphere Studies (SAS, including SENEX, SOAS, NOMADSS and SEAC4RS) conducted during the summer of 2013 provided an unprecedented opportunity for the atmospheric modeling community to come together to evaluate, diagnose and improve the representation of fundamental climate and air quality processes in models of varying temporal and spatial scales. This paper is aimed at discussing progress in evaluating, diagnosing and improving air quality and climate modeling using comparisons to SAS observations as a guide to thinking about improvements to mechanisms and parameterizations in models. The effort focused primarily on model representation of fundamental atmospheric processes that are essential to the formation of ozone, secondary organic aerosol (SOA) and other trace species in the troposphere, with the ultimate goal of understanding the radiative impacts of these species in the southeast and elsewhere. Here we address questions surrounding four key themes: gas-phase chemistry, aerosol chemistry, regional climate and chemistry interactions, and natural and anthropogenic emissions. We expect this review to serve as a guidance for future modeling efforts.
atmospheric chemistry↗
The Effect of Simulated Lunar Dust on the Absorptivity, Emissivity, and Operating Temperature on AZ-93 and Ag/FEP Thermal Control Surfaces
JSC-1AF lunar simulant has been applied to AZ-93 and AgFEP thermal control surfaces on aluminum or composite substrates in a simulated lunar environment. The temperature of these surfaces was monitored as they were heated with a solar simulator and cooled in a 30 K coldbox. Thermal modeling was used to determine the absorptivity ( ) and emissivity ( ) of the thermal control surfaces in both their clean and dusted states. Then, a known amount of power was applied to the samples while in the coldbox and the steady state temperatures measured. It was found that even a submonolayer of simulated lunar dust can significantly degrade the performance of both white paint and second-surface mirror type thermal control surfaces under these conditions. Contrary to earlier studies, dust was found to affect as well as . Dust lowered the emissivity by as much as 16 percent in the case of AZ-93, and raised it by as much as 11 percent in the case of AgFEP. The degradation of thermal control surface by dust as measured by / rose linearly regardless of the thermal control coating or substrate, and extrapolated to degradation by a factor 3 at full coverage by dust. Submonolayer coatings of dust were found to not significantly change the steady state temperature at which a shadowed thermal control surface will radiate.
Gaier, James R.↗
Solar Control on Jupiter's Equatorial X-ray Emissions: 26-29 November 2003 XMM-Newton Observation
During November 26-29,2003 XMM-Newton observed X-ray emissions from Jupiter for 69 hours. The 0.7-2.0 keV X-ray disk of Jupiter is observed to be brightest at the subsolar point, and limb darkening is seen in the 0.2-2.0 keV and 0.7-2.0 keV images. We present simultaneous lightcurves of Jovian equatorial X-rays and solar X-rays measured by the GOES, SOHO/SEM, and TIMED/SEE satellites. The solar X-ray flares occurring on the Jupiter-facing side of the Sun are matched by corresponding features in the Jovian X- rays. These results support the hypothesis that X-ray emissions from Jovian low-latitudes are solar X-rays scattered and fluoresced from the planet's upper atmosphere, and confirm that the Sun directly controls the non-auroral X-rays fiom Jupiter's disk. Our study suggest that Jovian equatorial X-rays; during certain Jupiter phase, can be used to predict the occurrence of solar flare on the hemisphere of the Sun that is invisible to space weather satellites.
Bhardwaj, Anil↗
Interpreting machine learning prediction of fire emissions and comparison with FireMIP process-based models
Annual burned areas in the United States have increased 2-fold during the past decades. With more large fires resulting in more emissions of fine particulate matter, an accurate prediction of fire emissions is critical for quantifying the impacts of fires on air quality, human health, and climate. This study aims to construct a machine learning (ML) model with game-theory interpretation to predict monthly fire emissions over the contiguous US (CONUS) and to understand the controlling factors of fire emissions. The optimized ML model is used to diagnose the process-based models in the Fire Modeling Intercomparison Project (FireMIP) to inform future development. Results show promising performance for the ML model, Community Land Model (CLM), and Joint UK Land Environment Simulator-Interactive Fire And Emission Algorithm For Natural Environments (JULES-INFERNO) in reproducing the spatial distributions, seasonality, and interannual variability of fire emissions over the CONUS. Regional analysis shows that only the ML model and CLM simulate the realistic interannual variability of fire emissions for most of the subregions (r >0.95 for ML and r =0.14~0.70 for CLM), except for Mediterranean California, where all the models perform poorly (r =0.74 for ML and r <0.30 for the FireMIP models). Regarding seasonality, most models capture the peak emission in July over the western US. However, all models except for the ML model fail to reproduce the bimodal peaks in July and October over Mediterranean California, which may be explained by the smaller wind speeds of the atmospheric forcing data during Santa Ana wind events and limitations in model parameterizations for capturing the effects of Santa Ana winds on fire activity. Furthermore, most models struggle to capture the spring peak in emissions in the southeastern US, probably due to underrepresentation of human effects and the influences of winter dryness on fires in the models. As for extreme events, both the ML model and CLM successfully reproduce the frequency map of extreme emission occurrence but overestimate the number of months with extremely large fire emissions. Comparing the fire PM 2.5 emissions from the ML model with process-based fire models highlights their strengths and uncertainties for regional analysis and prediction and provides useful insights into future directions for model improvements.
54 ENVIRONMENTAL SCIENCES↗
Nanoscale optical tomography with cathodoluminescence spectroscopy
In one aspect, a cathodoluminescence (CL) spectroscopic tomography device includes a sample stage to support a sample. An electron beam source scans an electron beam over the sample to yield light emission by the sample. A reflective element directs the light emission by the sample to a light detector. A controller controls operation of the sample stage, the electron beam source, and the light detector. In one aspect, a CL spectroscopic tomography device includes an electron beam source which directs an electron beam at an object to yield an emission by the object. A detector detects the emission. A controller receives information from the detector related to the detected emission. The controller derives a two-dimensional (2D) CL map from the information related to the detected emission, and derives a three-dimensional (3D) CL tomogram from the 2D CL map.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Is a Generator the Only Solution When the Grid Fails? Optimizing Systems for Resiliency and Carbon Reduction: Preprint
Traditionally, buildings are dependent on utility infrastructure, and when a grid failure happens, end users rely on the closest source of energy storage to sustain operation until power is restored. For buildings, that typically means using an electric generator. This electric generator either uses on-site energy storage such as fossil fuels in a tank or a gas connection which is, in turn, tied to gas wells—also a form of energy storage. Generators are popular for their ease of implementation and low capital costs; however, they have limited value outside of disruptions, and they are a source of scope 1 emissions, or direct greenhouse gas emissions from sources controlled by the building owner. In contrast, some power generation and storage systems, such as photovoltaic (PV) panels and battery energy storage systems (BESS), can serve the same purpose during grid disruptions while presenting advantages outside of power failure. This paper explores methods for storing and converting energy on-site to increase building resiliency, focusing on solutions that minimize scope 1 emissions. We analyze the cost and carbon impacts of energy efficiency measures, PV arrays, and BESS, with and without generators, in a simulation test case. We find significant benefits can be achieved both during and outside of power failure events when designing systems that integrate the on-demand capability of generators, the low carbon energy supplied by PV, and the storage capabilities of BESS. Specifically, adding even minimal BESS and PV can result in downsizing the generator, increasing generator efficiency and requiring less fuel.
ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
Active Control of Spacecraft Charging
The concept of active control of spacecraft charging by charged particle emission is described. Active potential control experiments using the ATS-5 and ATS-6 geostationary spacecraft are discussed, and results of these experiments are presented. Previously reported results are summarized, and a guide to reports on these data are provided. Experimental evidence presented indicates that emission of electrons only is not effective in maintaining spacecraft potential near plasma potential for spacecraft with electrically insulating surfaces. Emission of a low energy plasma, however, is effective for this purpose.
Purvis, C. K.↗