Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Distributed model predictive 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.

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

At least 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Chemical Blast Standard (1 kg)

Chemical explosions create blast waves with large overpressure disturbances. It is important to develop a standard blast model based on data to accurately predict acoustic blast-wave amplitudes near detonations and invert for explosion energy from distant observations of blast-wave signals. However, open data from large, controlled chemical explosions with reliable ground truth can be challenging to find. The lack of access to such data could limit the number of contributions to related research and potentially stifle the rate of discoveries or validation of existing models. Here, to address these data scarcity problem, we have curated and compiled a standardized set of 817 blast-wave waveforms from 19 distinct high-explosive events. The blast-wave waveforms are standardized to a 1 kg trinitrotoluene explosion using scaling laws and corrections for location effects. A brief overview of the dataset is presented along with explosion feature models as well as recommendations for extracting explosion features. The resulting dataset is distributed to an open repository in both Seismic Analysis Code and pandas DataFrame formats containing the waveforms, the scaled distances, and the sample rates.

58 GEOSCIENCES↗
DOE OSTI2018

Predictive performance modeling framework for a novel enclosed particle receiver configuration and application for thermochemical energy storage

Concentrating solar power (CSP) plants can provide dispatchable power with a thermal energy storage capability for increased renewable-energy grid penetration. Particle-based CSP systems permit higher temperatures, and thus, potentially higher solar-to-electric efficiency than state-of-the-art molten-salt heat-transfer systems. This paper describes a detailed numerical analysis framework for estimating the performance of a novel, geometrically complex, enclosed particle receiver design. The receiver configuration uses arrays of small tubular absorbers to collect and subsequently transfer solar energy to a flowing particulate medium. The enclosed nature of the receiver design renders it amenable to either an inert heat-transfer medium, or a reactive heat-transfer medium that requires a controllable ambient environment. The numerical analysis framework described in this study is demonstrated for the case of thermal reduction of CaCr 0.1 Mn 0.9 O 3-$\delta$ for thermochemical energy storage. The modeling strategy consists of Monte Carlo ray tracing for absorbed solar-energy distributions from a surround heliostat field, computational fluid dynamics modeling of small-scale local tubular arrays, surrogate response surfaces that approximately capture simulated tubular array performance, a quasi-two-dimensional reduced-order description of counter-flow reactive solids and purge gas, and a radiative exchange model applied to embedded-cavity structures at the size scale of the full receiver. In this work we apply the numerical analysis strategy to a single receiver configuration, but the framework can be generically applicable to alternative enclosed designs. In conclusion, we assess sensitivity of receiver performance to surface optical properties, heat-transfer coefficients, solids outlet temperature, and purge-gas feed rates, and discuss the significance of model assumptions and results for future receiver development.

14 SOLAR ENERGY↗
DOE OSTI2019

Experimental and Numerical Study of Coating Thickness Using Multi-slot Air Knives

Gas-jet wiping is a widely employed production technology for controlling the final zinc coating thickness on a moving substrate during continuous hot-dip galvanizing. This paper presents an experimental investigation and numerical analysis of a prototype multi-slot air knife, which offers an increase in wiping efficiency relative to the traditional single-slot jet geometry in the continuous galvanizing process. The applicability of the analytical coating weight model of Elsaadawy et al. (Metall Mater Trans B, 38:413-424, 2007) to predict the final coating weight was determined for the multi-slot geometry, where particular focus was devoted to the effect of geometric parameters. Experimental measurements under a variety of knife geometry and process conditions agreed with the coating weight predictions of the analytical model. It was also shown that the air-knife geometric parameters had a significant effect on the pressure profile and shear stress distribution applied by the air knives to the moving substrate. It was determined that the final coating thickness was significantly affected by the auxiliary jet width, D{sub a}, where lighter coating weights at higher strip velocities (up to 5.4 pct at V{sub s} = 1.5 m/s) could be achieved by using the multi-slot air-knives prototype vs. the conventional single-slot configuration.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Convergence in simulating global soil organic carbon by structurally different models after data assimilation

Abstract Current biogeochemical models produce carbon–climate feedback projections with large uncertainties, often attributed to their structural differences when simulating soil organic carbon (SOC) dynamics worldwide. However, choices of model parameter values that quantify the strength and represent properties of different soil carbon cycle processes could also contribute to model simulation uncertainties. Here, we demonstrate the critical role of using common observational data in reducing model uncertainty in estimates of global SOC storage. Two structurally different models featuring distinctive carbon pools, decomposition kinetics, and carbon transfer pathways simulate opposite global SOC distributions with their customary parameter values yet converge to similar results after being informed by the same global SOC database using a data assimilation approach. The converged spatial SOC simulations result from similar simulations in key model components such as carbon transfer efficiency, baseline decomposition rate, and environmental effects on carbon fluxes by these two models after data assimilation. Moreover, data assimilation results suggest equally effective simulations of SOC using models following either first‐order or Michaelis–Menten kinetics at the global scale. Nevertheless, a wider range of data with high‐quality control and assurance are needed to further constrain SOC dynamics simulations and reduce unconstrained parameters. New sets of data, such as microbial genomics‐function relationships, may also suggest novel structures to account for in future model development. Overall, our results highlight the importance of observational data in informing model development and constraining model predictions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

ISM EXCITATION AND METALLICITY OF STAR-FORMING GALAXIES AT Z ≃ 3.3 FROM NEAR-IR SPECTROSCOPY

We study the relationship between stellar mass, star formation rate (SFR), ionization state, and gas-phase metallicity for a sample of 41 normal star-forming galaxies at 3 ≲ z ≲ 3.7. The gas-phase oxygen abundance, ionization parameter, and electron density of ionized gas are derived from rest-frame optical strong emission lines measured on near-infrared spectra obtained with Keck/Multi-Object Spectrograph for Infra-Red Exploration. We remove the effect of these strong emission lines in the broadband fluxes to compute stellar masses via spectral energy distribution fitting, while the SFR is derived from the dust-corrected ultraviolet luminosity. The ionization parameter is weakly correlated with the specific SFR, but otherwise the ionization parameter and electron density do not correlate with other global galaxy properties such as stellar mass, SFR, and metallicity. The mass–metallicity relation (MZR) at z ≃ 3.3 shows lower metallicity by ≃0.7 dex than that at z = 0 at the same stellar mass. Our sample shows an offset by ≃0.3 dex from the locally defined mass–metallicity–SFR relation, indicating that simply extrapolating such a relation to higher redshift may predict an incorrect evolution of MZR. Furthermore, within the uncertainties we find no SFR–metallicity correlation, suggesting a less important role of SFR in controlling the metallicity at high redshift. We finally investigate the redshift evolution of the MZR by using the model by Lilly et al., finding that the observed evolution from z = 0 to z ≃ 3.3 can be accounted for by the model assuming a weak redshift evolution of the star formation efficiency.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2011

The Sensitivity of African Easterly Waves to Eastern Tropical Atlantic Sea-Surface Temperatures

The results of two regional atmospheric model simulations are compared to assess the influence of the eastern tropical Atlantic sea-surface temperature maximum on local precipitation, transient easterly waves and the West African summer monsoon. Both model simulations were initialized with reanalysis 2 data (US National Center for Environmental Prediction and Department of Energy) on 15 May 2006 and extended through 6 October 2006, forced by synchronous reanalysis 2 lateral boundary conditions introduced four times daily. One simulation uses 2006 reanalysis 2 sea-surface temperatures, also updated four times daily, while the second simulation considers ocean forcing absent the sea-surface temperature maximum, achieved here by subtracting 3 K at every ocean grid point between 0 and 15 N during the entire simulation. The simulation with 2006 sea-surface temperature forcing produces a realistic distribution of June-September mean precipitation and realistic westward propagating swaths of maximum rainfall, based on validation against Tropical Rainfall Measuring Mission (TRMM) estimates. The simulation without the sea-surface temperature maximum produces only 57% of the control June-September total precipitation over the eastern tropical Atlantic and about 83% of the Sahel precipitation. The simulation with warmer ocean temperatures generates generally stronger circulation, which in turn enhances precipitation by increasing moisture convergence. Some local precipitation enhancement is also attributed to lower vertical thermal stability above the warm water. The study shows that the eastern tropical Atlantic sea-surface temperature maximum enhances the strength of transient easterly waves and broadens the spatial extent of associated precipitation. However, large-scale circulation and its interaction with the African continent, and not sea-surface temperatures, control the timing and trajectories of the waves.

Druyan, Leonard M.↗
DOE OSTI2018

Large-Signal Impedance Modeling of Three-Phase Voltage Source Converters

Resonance problems have become a major hurdle in the large-scale grid integration of renewable energy. It is important to be able to predict the amplitude of resonance-induced distortions for the protection and control design of power electronic converters. We recently presented an impedance-based approach for the prediction of resonance amplitude. It was shown that the impedance response of a converter starts changing with the amplitude of resonance; this blocks the amplitude growth beyond a certain point where the converter forms a limit cycle mode of sustained oscillations. The large-signal impedance of a converter captures the change in its impedance response with the resonance amplitude, and it can be used to predict the resonance amplitude under different operation conditions. This paper presents large-signal sequence impedance modeling for three-phase voltage source converters (VSC) with dq-current control and PLL. Modeling challenges encountered in the absence of the small-signal approximation are addressed by a) leveraging the dominating influence of hard nonlinearities such as pulse-width modulation saturation and limiters over soft nonlinearities in shaping the converter large-signal behavior and b) modeling the large-signal gain of hard nonlinearities using appropriate describing functions. Developed large-signal impedance models are validated using numerical simulations. Measurements of the large-signal impedance responses of a commercial 1-MW VSC-based inverter are also presented to experimentally demonstrate the effects of the injected perturbation amplitude on impedance response as predicted by the developed model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Smart detection of indoor occupant thermal state via infrared thermography, computer vision, and machine learning

The ability to measure occupants’ thermal state in real time will enable major advances in the control of air conditioning systems. This study proposes predicting occupant thermal state by a combination of infrared thermography, computer vision, and machine learning. The approach (1) uses cheek, nose, and hand temperatures because they are least subject to blockage by hair, glasses, and clothing; (2) measures the distribution of skin temperatures within geometrically defined sub-areas of the face and hand; and (3) uses temperature differences within and between these areas to eliminate the effects of calibration drift that are unavoidable in thermal infrared (TIR) cameras. Two series of tests were conducted, respectively in an outdoor carport and an indoor environmental chamber, collecting a total of 48,422 sets of cheek, nose, and hand skin temperatures using a TIR camera and computer-vision technology, coupled with 715 subjective responses of thermal sensations. To predict occupant thermal state, Random Forest classification models were built using either absolute skin temperatures (the maximum and median temperatures of cheek and hand segments, and the temperature of the central spot on the nose), or intra- and inter-segment temperature differences of cheeks, hands, and nose. These measurements were found to accurately predict occupant thermal state. Using the maximum and median temperatures for cheek and nose, or for cheek and hand, predicts thermal state with an accuracy of 92–96%. In conclusion, using only the intra- and inter-segment temperature differences from cheek and nose is 83% accurate; adding the hand temperature differences increases the accuracy to 96%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2005

Solar Cycle/Seasonal Variations of H, D, H2 and He Distributions and Escape on Mars as Determined by the Mars Thermosphere Global Circulation Model (MTGCM)

The Mars Thermosphere General Circulation Model (MTGCM) was exercised for Ls = 90 (aphelion) solar minimum, and Ls = 270 perihelion) solar maximum conditions. Simulated MTGCM outputs (i.e. helium density distributions) were compared to those previously observed for Earth and Venus. Winter polar night bulges of helium are predicted on Mars, similar to those observed on the nightside of Venus and in the winter polar regions of Earth. A poster on this research was presented at the European Geophysical Society Meeting (EGS) in 2003. This research paves the way for what might be expected in the polar night regions of Mars during upcoming aerobraking and mapping Campaigns. Lastly, Mars thermosphere (approx. 100-130 km) winter polar warming was observed at high Northern latitudes during the perihelion season, but not at high Southern latitudes during the opposite aphelion season. Presumably, the Mars thermospheric circulation is responsible for the dynamically controlled heating needed to warm polar night temperatures above radiative equilibrium values. Again, MTGCM simulations were conducted for Ls = 90 and Ls = 270 conditions; polar temperatures were examined and found to be much warmer at Northern high latitudes (perihelion) than at Southern high latitudes (aphelion), similar to Mars aerobraking datasets. The Mars thermospheric circulation is found to be stronger during perihelion solstice conditions than during aphelion conditions, owing to both stronger seasonal solar and dust heating during Mars perihelion. An invited talk was given at the Spring AGU 2004 on this research. A forthcoming GRL paper was drafted on this same topic, but not submitted before the termination of this 1-year grant.

Bougher, Stephen↗
DOE OSTI2019

Automated electrical demand peak leveling in a manufacturing facility with short term energy storage for smart grid participation

Demand side management of energy is a vital function in the smart grid that allows for greater integration of renewable energy resources, and is facilitated with economic incentives in energy and demand pricing schedules. Manufacturing systems can take advantage of these incentives to reduce their energy costs through active energy management. This paper is a simulation analysis on the implementation of a novel algorithm that levelizes the maximum power load of an industrial bakery that operates under an on-peak demand price structure. The algorithm takes advantage of an untapped thermal energy storage resource in the facility, a chilled glycol buffer tank, to level the short intra-day power oscillations that the facility experiences. One of the key advantages of the algorithm is that it does not require precise demand forecasting or complex control algorithms, such as model predictive control. Even with substantial error in peak power estimates (5%), the algorithm is expected to result in at least a 2% peak reduction. Under ideal prediction, the algorithm reduces the on-peak facility power maximum by 7.3% of the possible 9.0% reduction the storage can provide. Further, the algorithm uses very few facility specific inputs, and can readily be adapted for any facility with short intra-day oscillatory power profiles and untapped storage capacity. The key insight of the paper is the employment of a novel algorithm to leverage untapped energy storage in manufacturing facilities to transform them into smart grid participants with no major capital investment.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Control of Weld Residual Stress in a Thin Steel Plate through Low Transformation Temperature Welding Consumables

Low transformation temperature welding (LTTW) consumables are characterized by a low martensite start temperature and a large fraction of martensite forming in the weld. It can efficiently reduce the tensile residual stress because the volume expansion associated with the martensitic transformation compensates for the thermal contraction during cooling. In this work, a LTTW wire, designated as EH200B, was created for the arc welding of advanced high-strength steel thin plates. In comparison to conventional ER70S-3 wires, this LTTW wire generated an opposite distortion pattern. Neutron diffraction measurements along the center thickness of the welded plates showed the maximum residual stress along the longitudinal direction (LD) in the weld region, and the heat-affected zone (HAZ) immediately adjacent to the weld region was reduced from ~330 MPa to below 240 MPa by using the LTTW wire. A finite element (FE) model was developed to predict the residual stress distributions of the plates welded under these two wires. The simulation results showed reasonable agreement with the volume-average neutron diffraction data. Compressive residual stress in the weld region using the LTTW wire was predicted by the FE method. Electron backscattered diffraction and x-ray diffraction measurements confirmed ~90% martensite was present in the LTTW weld. The fatigue life of DP980 steel lap joint panels using EH200B wire nearly doubled that of ER70S-3 wire. This improvement was attributed to the high strength and low LD residual stress in the weld and HAZ immediately adjacent to the weld.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Tidal Stream Energy Resource Characterization in the Salish Sea

Tidal stream energy holds great potential as a renewable energy source in regions of the world where tidal currents are strong and predictable. The tidal stream energy resource of a region is strongly controlled by its tidal wave characteristics, the local bathymetry, and coastal geometric features. The Salish Sea, a large estuary on the Pacific Northwest coast, represents a great tidal stream resource because of its strong tidal currents in many tidal channels. However, the tidal resource in the Salish Sea has not been systematically characterized, primarily because of its large area and complex bathymetry and coastlines. This paper presents a modeling study conducted to characterize the tidal energy resource of the Salish Sea based on a high-resolution three-dimensional tidal hydrodynamic model of the Salish Sea, which was extensively validated using data derived from 10 tidal gauge stations and 132 Acoustic Doppler Current Profiler stations. Model validation results indicated the Salish Sea hydrodynamic model is skillful in simulating tidal wave propagation and velocity distributions in the Salish Sea. Based on model results, a total of 16 tidal channels with strong tidal currents, 9 in the San Juan Islands and Rosario Strait regions and 7 in the Puget Sound, were identified as hotspots for potential tidal energy development. Velocity probability distributions and exceedance curves of cross-channel average velocity magnitudes were calculated at all 16 channels based on the recommendations of the International Electrotechnical Commission Technical Specifications for tidal energy resource characterization. The tidal energy resource at the 16 hotspots was also characterized using power density distributions and kinetic energy fluxes. The ranking of the kinetic energy fluxes suggested that Admiralty Inlet, Rosario Strait, and Middle Channel are the top three hotspot sites in the Salish Sea for tidal stream energy development. The study demonstrated the need for a high-resolution 3-D modeling framework for accurate simulation of tidal currents in large complex estuarine systems, in the context of tidal energy resource characterization.

tidal stream energy, resource characterization, Sa↗
DOE OSTI2022

Description of global EGAM in the maximum of local frequency during current ramp-up discharges in DIII-D

Energetic-particle-induced geodesic acoustic modes, EGAMs (Fu, Phys. Rev. Let., vol. 101, 2008, pp. 185002), driven by neutral beam injection (NBI), have been observed in many DIII-D tokamak experiments (Nazikian et al., Phys. Rev. Lett., vol. 101, 2008, pp. 185001). This mechanism has been theoretically investigated in (Qiu et al., Plasma Phys. Control. Fusion, vol. 52, 2010, pp. 095003), using a sharp energetic particle distribution function, and in (Qu et al., Plasma Phys. Control. Fusion, vol. 59, 2017, pp. 055018), where the dispersion relation and eigenmode behaviour were obtained for the situation of early beam scenario, that is, for times smaller than the beam slowing down time. In this work, we extend these studies determining the eigenmode for beyond the slowing down time, in a scenario with reverse safety factor q profile, where a small concentration of energetic ions can produce an off-axis maximum in the GAM dispersion relation. Here, the characteristics of EGAM are analytically studied with the drift kinetic equation together with the MHD code NOVA. The toroidal energetic ion transit frequency, coupled with the GAM frequency, produces the maximum in the dispersion relation where the eigenmode can be found. The quantitative correspondence of experimental results with the predictions of the proposed model is analysed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

An Advanced Microscopic Energy Consumption Model for Automated Vehicle:Development, Calibration, Verification

The automated vehicle (AV) equipped with the Adaptive Cruise Control (ACC) system is expected to reduce the fuel consumption for the intelligent transportation system. This paper presents the Advanced ACC-Micro (AA-Micro) model, a new energy consumption model based on micro trajectory data, calibrated and verified by empirical data. Utilizing a commercial AV equipped with the ACC system as the test platform, experiments were conducted at the Columbus 151 Speedway, capturing data from multiple ACC and Human-Driven (HV) test runs. The calibrated AA-Micro model integrates features from traditional energy consumption models and demonstrates superior goodness of fit, achieving an impressive 90% accuracy in predicting ACC system energy consumption without overfitting. A comprehensive statistical evaluation of the AA-Micro model's applicability and adaptability in predicting energy consumption and vehicle trajectories indicated strong model consistency and reliability for ACC vehicles, evidenced by minimal variance in RMSE values and uniform RSS distributions. Conversely, significant discrepancies were observed when applying the model to HV data, underscoring the necessity for specialized models to accurately predict energy consumption for HV and ACC systems, potentially due to their distinct energy consumption characteristics.

Ma, Ke↗
DOE OSTI2023

Bentonite buffer under high temperature: laboratory experiments and coupled process modeling

Abstract. Bentonite buffer in a geological repository will be simultaneously heated from decaying radioactive waste and hydrated from the surrounding host rock, triggering complex and coupled THMC (thermal–hydrological–mechanical–chemical) processes. Understanding the THMC behavior of bentonite-based engineered barrier system (EBS) is key to the evaluation and prediction of its long-term performance. Studies on the THMC process have been focused on conditions under 100 ∘C, as most design concepts impose a thermal limit of 100 ∘C in bentonite. Recently, studies under high-temperature conditions have been conducted to evaluate the possibility of raising the thermal limit and expanding the data/knowledge base to increase the confidence level. In this abstract, we present a series of bench-scale laboratory experiments at high temperatures (up to 200 ∘C) and the corresponding modeling work. Two sets of column tests were conducted, and each set consisted of two test columns: a control column undergoing only hydration (non-heated) and an experiment column experiencing both heating and hydration (heated). During the experiment, frequent X-ray computed tomography (CT) images were collected to provide a 3D visualization of the density distribution and present the spatiotemporal evolution of (1) hydration/dehydration, (2) clay swelling/shrinkage, (3) displacement, and (4) mineral precipitation. The two sets of tests differ with respect to several experimental conditions, such as bentonite type, compacted density and water content, water chemistry, and hydration pressure, but the important difference is that the first set used bentonite powder with a dry density of 1.28 g cm−3, whereas the second set used granulated bentonite (mixture of pellets and powder) with a dry density of 1.45–1.5 g cm−3. In both sets of experiments, a comprehensive post-dismantling characterization of bentonite samples was carried out after the column tests had been running for 1.5 years. Comparing non-heated and heated columns, the temperature gradient led to lower degree of homogenization of bentonite after bentonite became fully saturated; comparing the first and second sets, granulated and powdered bentonite exhibited drastically different hydration behavior. A THM model with a 2D axisymmetric grid system was used to interpret the data from the first set of tests. The model considers the combined impact of saturation, fluid pressure, and porosity change due to swelling/compression on the spatiotemporal distribution of bulk density and movement of the thermocouple modules. Observations from the tests help us understand the early perturbation of bentonite buffer under high temperature, and data from these tests improve the calibration of key constitutive hydrological and mechanical models and, therefore, enhance the modeling capability with respect to calculating the long-term evolution of bentonite buffer.

Zheng, Liange↗
DOE OSTI2018

Model Identification of Inverter Nonlinear Control Dynamics

To comprehensively predict in silico potential disruptive dynamic performance of converter-based generation and develop solutions, the application of electromagnetic transient programs is desirable. However, these accurate simulations highly depend on inverter models of actual field implementations, which are often unavailable because they are proprietary. To address this problem, we propose a time-domain model identification method that can be used to determine the control models of inverters in continuous time from multiple experimental studies. The focus is on identifying the dynamic representation of controls because they dominate the dynamic response of renewable assets. To illustrate the applicability of the technique, we consider a subclass of inverter controllers for autonomous grid applications that rely on nonlinear oscillators.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Improving the Representation of Soluble Iron in Climate Models

Mineral dust produced in the arid and semi-arid regions of the world is the dominant source of iron (Fe) in atmospheric aerosol inputs to the open ocean. The bioavailable Fe fraction of atmospheric dust is thought to regulate and occasionally limit the primary productivity in large oceanic regions, which influences the CO2 uptake from the atmosphere affecting the Earth’s climate. Because Fe bioavailability cannot be directly measured, it is assumed that the dissolved Fe or highly reactive Fe in the dust is bioavailable. The fraction of soluble Fe in dust is mainly controlled by: (1) the mineral composition of the soils and the emitted dust from the source areas; (2) the atmospheric processing that converts the Fe in Fe-bearing minerals into highly soluble forms of Fe. The project has mainly focused on constraining the mineral composition of dust aerosols (1), a previously neglected, yet a key issue to constrain the deposition of soluble iron. Deriving aerosol mineral composition requires global knowledge of the soil mineral content, which is available from poorly constrained global atlases. In addition, the mineral content of the emitted aerosol differs from that of the parent soil. Measurements of soil mineral fractions are based upon wet sedimentation (or ’wet sieving’) techniques that disturb the soil sample, breaking aggregates that are found in the original, undispersed soil that is subject to wind erosion. Wet sieving alters the soil size distribution, replacing aggregates that are potentially mobilized as aerosols with a collection of smaller particles. A major challenge is to derive the size-distributed mineral fractions of the emitted dust based upon their fractions measured from wet-sieved soils. Finally, representations of dust mineral composition need to account for mixtures of minerals. Examination of individual particles shows that iron, an element that is central to many climate processes, is often found as trace impurities of iron oxide attached to aggregates of other minerals. This is another challenge that has been tackled by the project. The project has produced a major step forward on our understanding of the key processes needed to predict the mineral composition of dust aerosols by connecting theory, modeling and observations. The project has produced novel semi-empirical and theoretical methods to estimate the emitted size distribution and mineral composition of dust aerosols. These methods account for soil aggregates that are potentially emitted from the original undisturbed soil but are destroyed during wet sieving. The methods construct the emitted size distribution of individual minerals building upon brittle fragmentation theory, reconstructions of wet-sieved soil mineral size distributions, and/or characteristic mineral size distributions estimated from observations at times of high concentration. Based on an unprecedented evaluation with a new global compilation of observations produced with the project support, we showed that the new methods remedy some key deficiencies compared to the previous state-of-the-art. This includes the correct representation of Fe-bearing phyllosilicates at silt sizes, where they are abundant according to observations. In addition, the quartz fraction of silt particles is in better agreement with measured values. In addition, we represent an additional class of iron oxide aerosol that is a small impurity embedded within other minerals, allowing it to travel farther than in its pure crystalline state. We assume that these impurities are least frequent in soils rich in iron oxides (as a result of the assumed effect of weathering that creates pure iron oxide crystals). The mineral composition of dust is also important to other interaction with climate - through shortwave absorption and radiative forcing, nucleation of cloud droplets and ice crystals, and the heterogeneous formation of sulfates and nitrates - and to its impacts upon human health. Despite the importance of mineral composition, models have typically assumed that soil dust aerosols have globally uniform composition. The results of this project will allow an improved estimation of the dust effects upon climate and health.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Novel stochastic methods to predict short-term solar radiation and photovoltaic power

Solar forecasting has evolved towards becoming a key component of economical realization of high penetration levels of photovoltaic (PV) systems. This paper presents two novel stochastic forecasting models for solar PV by utilizing historical measurement data to outline a short-term high-resolution probabilistic behavior of solar. First, an uncertain basis functions method is used to forecast both solar radiation and PV power. Three possible distributions are considered for the uncertain basis functions - Gaussian, Laplace, and Uniform distributions. Second, stochastic state-space models are applied to characterize the behaviors of solar radiation and PV power output. A filter-based expectation-maximization and Kalman filtering mechanism is employed to recursively estimate the system parameters and state variables. This enables the system to accurately forecast small as well as large fluctuations of the solar signals. The introduced forecasting models are suitable for real-time tertiary dispatch controllers and optimal power controllers. The PV forecasting models are tested using solar radiation and PV power measurement data collected from a 13.5 kW PV panel installed on the rooftop of our laboratory. Furthermore, the results are compared with standard time series forecasting mechanisms and show a substantial improvement in the forecasting accuracy of the total energy produced.

14 SOLAR ENERGY↗