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At least 739 records · Page 41

A general spatial-temporal framework for short-term building temperature forecasting at arbitrary locations with crowdsourcing weather data

Weather forecasting has been a critical component to predict and control building energy consumption for better building energy management. Without accessibility to other data sources, the onsite observed temperatures or the airport temperatures are used in forecast models. In this paper, we present a novel approach by utilizing the crowdsourcing weather data from neighboring personal weather stations (PWS) to improve the weather forecast accuracy around buildings using a general spatial-temporal modeling framework. The final forecast is based on the ensemble of local forecasts for the target location using neighboring PWSs. Our approach is distinguished from existing literature in various aspects. First, we leverage the crowdsourcing weather data from PWS in addition to public data sources. In this way, the data is at much finer time resolution (e.g., at 5-minute frequency) and spatial resolution (e.g., arbitrary location vs grid). Second, our proposed model incorporates spatial-temporal correlation information of weather variables between the target building and a set of neighboring PWSs so that underlying correlations can be effectively captured to improve forecasting performance. Here, we demonstrate the performance of the proposed framework by comparing to the benchmark models on temperature forecasting for a building located at an arbitrary location at San Antonio, Texas, USA. In general, the proposed model framework equipped with machine learning technique such as Random Forest can improve forecasting by 50% compares with persistent model and has 90% chance to outperform airport forecast in short-term forecasting. In a real-time setting, the proposed model framework can provide more accurate temperature forecasting results compared with using airport temperature forecast for most forecast horizon. Moreover, we analyze the sensitivity of model parameters to gain insights on how crowdsourcing data from the neighboring personal weather stations impacts forecasting performance. Finally, we implement our model in other cities such as Syracuse and Chicago to test the model's performance in different landforms and climate types.

54 ENVIRONMENTAL SCIENCES↗

Revealing the critical role of radical-involved pathways in high temperature cyclopentanone pyrolysis

Cyclopentanone (CPO) is a promising biofuel for spark-ignition engines due to its ring strain and high auto-ignition resistance. Understanding CPO decomposition is crucial for building a high-temperature combustion model. Here we present a comprehensive kinetic model for high-temperature pyrolysis of CPO with verified results from high-pressure shock tube (HPST) measurements. The time- histories of carbon monoxide (CO), ethylene (C 2 H 4 ), and CPO absorbances over the temperature range of 1156-1416 K and pressure range of 8.53-10.06 atm were measured during current experiments. A corresponding detailed kinetic model was generated using the Reaction Mechanism Generator (RMG) with dominant unimolecular/radical-involved decomposition pathways from either previous studies or quantum calculations within the current work. The obtained model containing 821 species and 79,859 reactions exhibited a good agreement with the experimental results. In this study, the absorbance ratio between C 2 H 4 and CO was used as an important factor to validate models and to prove that radical-involved bimolecular pathways were as significant as unimolecular decomposition of CPO. The rate of production (ROP) analysis showed H radicals play a major role in the decomposition, and the whole decomposition process could be divided into three stages based on the H radical concentration. Finally, the insights from present work can be used to generate a better CPO combustion model and help evaluate CPO as an advanced biofuel.

09 BIOMASS FUELS↗

Basal melt beneath whillans ice stream and ice streams A and C

We have used a recently derived map of the velocity of Whillans Ice Stream and Ice Streams A and C to help estimate basal melt. Temperature was modeled with a simple vertical advection-diffusion equation, 'tuned' to match temperature profiles. We find that most of the melt occurs beneath the tributaries where larger basal shear stresses and thicker ice favors greater melt (e.g., 10-20 mm/yr). The occurrence of basal freezing is predicted beneath much of the ice plains of Ice Stream C and Whillans Ice Stream. Modelled melt rates for when Ice Stream C was active suggest there was just enough melt water generated in its tributaries to balance basal freezing on its ice plain. Net basal melt for Whillans Ice Stream is positive due to smaller basal temperature gradients. Modelled temperatures on Whillans Ice Stream, however, were constrained by a single temperature profile at UpB. Basal temperature gradients for Whillans B1 and Ice Stream A may have conditions more similar to those beneath Ice Streams C and D, in which case, there may not be sufficient melt to sustain motion. This would be consistent with the steady deceleration of Whillans stream over the last few decades.

glaciers ice sheets↗

Fort Bliss Geothermal Area Data: Temperature profile, logs, schematic model and cross section

This dataset contains a variety of data about the Fort Bliss geothermal area, part of the southern portion of the Tularosa Basin, New Mexico. The dataset contains schematic models for the McGregor Geothermal System, a shallow temperature survey of the Fort Bliss geothermal area. The dataset also contains Century OH logs, a full temperature profile, and complete logs from well RMI 56-5, including resistivity and porosity data, drill logs with drill rate, depth, lithology, mineralogy, fractures, temperature, pit total, gases, and descriptions among other measurements as well as CDL, CNL, DIL, GR Caliper and Temperature files. A shallow (2 meter depth) temperature survey of the Fort Bliss geothermal area with 63 data points is also included. Two cross sections through the Fort Bliss area, also included, show well position and depth. The surface map included shows faults and well spatial distribution. Inferred and observed fault distributions from gravity surveys around the Fort Bliss geothermal area.

15 GEOTHERMAL ENERGY↗

Simple Spreadsheet Thermal Models for Cryogenic Applications

Self consistent circuit analog thermal models that can be run in commercial spreadsheet programs on personal computers have been created to calculate the cooldown and steady state performance of cryogen cooled Dewars. The models include temperature dependent conduction and radiation effects. The outputs of the models provide temperature distribution and Dewar performance information. these models have been used to analyze the SIRTF Telescope Test Facility (STTF). The facility has been brought on line for its first user, the Infrared Telescope Technology Testbed (ITTT), for the Space Infrared Telescope Facility (SIRTF) at JPL. The model algorithm as well as a comparison between the models' predictions and actual performance of this facility will be presented.

spreadsheet thermal model cryogenic↗

(abstract) Simple Spreadsheet Thermal Models for Cryogenic Applications

Self consistent circuit analog thermal models, that can be run in commercial spreadsheet programs on personal computers, have been created to calculate the cooldown and steady state performance of cryogen cooled Dewars. The models include temperature dependent conduction and radiation effects. The outputs of the models provide temperature distribution and Dewar performance information. These models have been used to analyze the Cryogenic Telescope Test Facility (CTTF). The facility will be on line in early 1995 for its first user, the Infrared Telescope Technology Testbed (ITTT), for the Space Infrared Telescope Facility (SIRTF) at JPL. The model algorithm as well as a comparison of the model predictions and actual performance of this facility will be presented.

cryogenic thermal model cryostat SIRTF↗

Approach to the Steady State in Kinetic Models with Thermal Reservoirs at Different Temperatures

We continue the investigation of kinetic models of a system in contact via stochastic interactions with several spatially homogeneous thermal reservoirs at different temperatures. Considering models different from those investigated in Carlen et al. (Braz J Probab Stat 29:372–386, 2015), we explicitly compute the unique spatially uniform non-equilibrium steady state (NESS) and prove that it is approached exponentially fast from any uniform initial state. This leaves open the question of whether there exist NESS that are not spatially uniform. Making a further simplification of our models, we then prove non-existence of such NESS and exponential approach to the unique spatially uniform NESS (with a computably boundable rate). The method of proof relies on refined Doeblin estimates and other probabilistic techniques, and is quite different form the analysis in Carlen et al. (Braz J Probab Stat 29:372–386, 2015) that was based on contraction mapping methods.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A hybrid building thermal modeling approach for predicting temperatures in typical, detached, two-story houses

Within the residential building sector, the air-conditioning (AC) load is the main target for peak load shifting and reduction since it is the largest contributor to peak demand. By leveraging its power flexibility, residential AC is a good candidate to provide building demand response and peak load shifting. For realization of accurate and reliable control of AC loads, a building thermal model, which characterizes the properties of a building’s envelope and its thermal mass, is an essential component for accurate indoor temperature or cooling/heating demand prediction. Building thermal models include two types: “Forward” and “Data-Driven”. Due to time-saving and cost-effective characteristics, different data-driven models have been developed in a number of research studies. However, few developed models can predict temperatures in respective zones of a multiple-zone building with an open air path between zones e.g., an open stairwell connecting two floors of a home. In this research, a novel hybrid modeling approach is proposed to predict the average indoor air temperatures of both the upstairs and downstairs. This “hybrid” solution integrates both gray-box, i.e. RC model and black-box models. A developed RC model is used to predict the building mean temperature, and black-box model, in which the supervised machine learning algorithms are leveraged, is used to predict the temperature difference between the downstairs and upstairs. Compared with the measured data from a real house, the results obtained have acceptable/satisfactory accuracy. The method proposed in this study integrates the advantages of black-box and gray-box modeling. As a result, it can be used as a reliable alternative to predict the average temperatures in respective floors of typical detached two-story houses.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Impact of Sequential Ammonia Fiber Expansion (AFEX) Pretreatment and Pelletization on the Moisture Sorption Properties of Corn Stover

Combining ammonia fiber expansion (AFEX™) pretreatment with a depot processing facility is a promising option for delivering high-value densified biomass to the emerging bioenergy industry. However, because the pretreatment process results in a high moisture material unsuitable for pelleting or storage (40% wet basis), the biomass must be immediately dried. If AFEX pretreatment results in a material that is difficult to dry, the economics of this already costly operation would be at risk. This work tests the nature of moisture sorption isotherms and thin-layer drying behavior of corn (Zea mays L.) stover at 20°C to 60°C before and after sequential AFEX pretreatment and pelletization to determine whether any negative impacts to material drying or storage may result from the AFEX process. The equilibrium moisture content to equilibrium relative humidity relationship for each of the materials was determined using dynamic vapor sorption isotherms and modeled with modified Chung-Pfost, modified Halsey, and modified Henderson temperature-dependent models as well as the Double Log Polynomial (DLP), Peleg, and Guggenheim Anderson de Boer (GAB) temperature-independent models. Drying kinetics were quantified under thin-layer laboratory testing and modeled using the Modified Page's equation. Water activity isotherms for non-pelleted biomass were best modeled with the Peleg temperature-independent equation while isotherms for the pelleted biomass were best modeled with the Double Log Polynomial equation. Thin-layer drying results were accurately modeled with the Modified Page's equation. The results of this work indicate that AFEX pretreatment results in drying properties more favorable than or equal to that of raw corn stover, and pellets of superior physical stability in storage.

09 BIOMASS FUELS↗

Evaluating atmospheric correction models for retrieving surface temperatures from the AVHRR over a tallgrass prairie

The effects of atmospheric attenuation on surface radiative temperatures obtained by the AVHRR over a tallgrass prairie area in the Flint Hills of Kansas are examined. Six atmospheric correction models developed primarily for sea-surface temperature studies are used to test their utility for retrieval of radiative temperatures over the land surface. An uncertainty of + or - 3.0 C was found for the AVHRR data, and used to evaluate the performance of a given model. When the difference between in situ and AVHRR surface temperatures was smaller than the uncertainty, the model was judged to be adequate. Among the six models evaluated, only the NOAA split-window model consistently adjusted the AVHRR surface temperatures within + or - 3.0 C of the in situ measurements.

Cooper, D. I.↗

Modeling of Prismatic High Temperature Reactors in Pronghorn

Pronghorn is a MOOSE based thermal-hydraulics code developed at Idaho National Laboratory (INL) for advanced nuclear reactor analysis. It has been previously applied to model pebble-bed high temperature reactors (HTRs), liquid-metal cooled reactors, and molten salt reactors, among others. This work leverages the coarse-mesh modeling capabilities in Pronghorn to model the Oregon State University (OSU)'s High Temperature Test Facility (HTTF). The HTTF is a 1:4 height scaled-down facility of General Atomics' Modular High Temperature Gas-cooled Reactor (MHTGR). The facility is primarily built to generate data for code and model validation, and does not precisely replicate MHTGR conditions. Nevertheless, it encompasses the main physics associated with MHTGR transients.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Conjugate (solid/fluid) computational fluid dynamics analysis of the space shuttle solid rocket motor nozzle/case and case field joints

Three-dimensional, conjugate (solid/fluid) heat transfer analyses of new designs of the Solid Rocket Motor (SRM) nozzle/case and case field joints are described. The main focus was to predict the consequences of multiple rips (or debonds) in the ambient cure adhesive packed between the nozzle/case joint surfaces and the bond line between the mating field joint surfaces. The models calculate the transient temperature responses of the various materials neighboring postulated flow/leakpaths into, past, and out from the nozzle/case primary O-ring cavity and case field capture O-ring cavity. These results were used to assess if the design was failsafe (i.e., no potential O-ring erosion) and reusable (i.e., no excessive steel temperatures). The models are adaptions and extensions of the general purpose PHOENICS fluid dynamics code. A non-orthogonal coordinate system was employed and 11,592 control cells for the nozzle/case and 20,088 for the case field joints are used with non-uniform distribution. Physical properties of both fluid and solids are temperature dependent. A number of parametric studies were run for both joints with results showing temperature limits for reuse for the steel case on the nozzle joint being exceeded while the steel case temperatures for the field joint were not. O-ring temperatures for the nozzle joint predicted erosion while for the field joint they did not.

Doran, D.↗

Empirical model of global thermospheric temperature and composition based on data from the OGO-6 quadrupole mass spectrometer

An empirical global model for magnetically quiet conditions has been derived from longitudinally averaged N2, O, and He densities by means of an expansion in spherical harmonics. The data were obtained by the OGO-6 neutral mass spectrometer and cover the altitude range 400 to 600 km for the period 27 June 1969 to 13 May 1971. The accuracy of the analytical description is of the order of the experimental error for He and O and about three times experimental error for N2, thus providing a reasonable overall representation of the satellite observations. Two model schemes are used: one representing densities extrapolated to 450 km and one representing densities extrapolated to 120 km with exospheric temperatures inferred from N2 densities. Using the best fit model parameters the global thermospheric structure is presented in the form of a number of contour plots.

Hedin, A. E.↗

Constitutive Modeling of the High-Temperature Flow Behavior of α-Ti Alloy Tube

In the hot metal gas forming process, the deformation conditions, such as temperature, strain rate and deformation degree, are often prominently changed. The understanding of the flow behavior of α-Ti seamless tubes over a relatively wide range of temperatures and strain rates is important. In this study, the stress–strain curves in the temperature range of 973-1123 K and the initial strain rate range of 0.0004-0.4 s{sup −1} were measured by isothermal tensile tests to conduct a constitutive analysis and a deformation behavior analysis. The results show that the flow stress decreases with the decrease in the strain rate and the increase of the deformation temperature. The Fields–Backofen model and Fields–Backofen–Zhang model were used to describe the stress–strain curves. The Fields–Backofen–Zhang model shows better predictability on the flow stress than the Fields–Backofen model, but there exists a large deviation in the deformation condition of 0.4 s{sup −1}. A modified Fields–Backofen–Zhang model is proposed, in which a strain rate term is introduced. This modified Fields–Backofen–Zhang model gives a more accurate description of the flow stress variation under hot forming conditions with a higher strain rate up to 0.4 s{sup −1}. Accordingly, it is reasonable to adopt the modified Fields–Backofen–Zhang model for the hot forming process which is likely to reach a higher strain rate, such as 0.4 s{sup −1}.

36 MATERIALS SCIENCE↗

Multiscale Modeling of Ultra High Temperature Ceramics (UHTC) ZrB2 and HfB2: Application to Lattice Thermal Conductivity

We are developing a multiscale framework in computational modeling for the ultra high temperature ceramics (UHTC) ZrB2 and HfB2. These materials are characterized by high melting point, good strength, and reasonable oxidation resistance. They are candidate materials for a number of applications in extreme environments including sharp leading edges of hypersonic aircraft. In particular, we used a combination of ab initio methods, atomistic simulations and continuum computations to obtain insights into fundamental properties of these materials. Ab initio methods were used to compute basic structural, mechanical and thermal properties. From these results, a database was constructed to fit a Tersoff style interatomic potential suitable for atomistic simulations. These potentials were used to evaluate the lattice thermal conductivity of single crystals and the thermal resistance of simple grain boundaries. Finite element method (FEM) computations using atomistic results as inputs were performed with meshes constructed on SEM images thereby modeling the realistic microstructure. These continuum computations showed the reduction in thermal conductivity due to the grain boundary network.

Lawson, John W.↗

Regional evapotranspiration from an image-based implementation of the Surface Temperature Initiated Closure (STIC1.2) model and its validation across an aridity gradient in the conterminous US

Recent studies have highlighted the need for improved characterizations of aerodynamic conductance and temperature (g A and T 0 ) in thermal remote-sensing-based surface energy balance (SEB) models to reduce uncertainties in regional-scale evapotranspiration (ET) mapping. By integrating radiometric surface temperature (TR) into the Penman–Monteith (PM) equation and finding analytical solutions of gA and T0, this need was recently addressed by the Surface Temperature Initiated Closure (STIC) model. However, previous implementations of STIC were confined to the ecosystem-scale using flux tower observations of infrared temperature. This study demonstrates the first regional-scale implementation of the most recent version of the STIC model (STIC1.2) that integrates the Moderate Resolution Imaging Spectroradiometer (MODIS) derived TR and ancillary land surface variables in conjunction with NLDAS (North American Land Data Assimilation System) atmospheric variables into a combined structure of the PM and Shuttleworth–Wallace (SW) framework for estimating ET at 1 km × 1 km spatial resolution. Evaluation of STIC1.2 at 13 core AmeriFlux sites covering a broad spectrum of climates and biomes across an aridity gradient in the conterminous US suggests that STIC1.2 can provide spatially explicit ET maps with reliable accuracies from dry to wet extremes. When observed ET from one wet, one dry, and one normal precipitation year from all sites were combined, STIC1.2 explained 66 % of the variability in observed 8-day cumulative ET with a root mean square error (RMSE) of 7.4 mm/8-day, mean absolute error (MAE) of 5 mm/8-day, and percent bias (PBIAS) of -4 %. These error statistics showed relatively better accuracies than a widely used but previous version of the SEB-based Surface Energy Balance System (SEBS) model, which utilized a simple NDVI-based parameterization of surface roughness (z OM ), and the PM-based MOD16 ET. SEBS was found to overestimate (PBIAS = 28 %) and MOD16 was found to underestimate ET (PBIAS =-26 %). The performance of STIC1.2 was better in forest and grassland ecosystems as compared to cropland (20 % underestimation) and woody savanna (40 % overestimation). Model inter-comparison suggested that ET differences between the models are robustly correlated with g A and associated roughness length estimation uncertainties which are intrinsically connected to T R uncertainties, vapor pressure deficit (D A ), and vegetation cover. A consistent performance of STIC1.2 in a broad range of hydrological and biome categories, as well as the capacity to capture spatio-temporal ET signatures across an aridity gradient, points to the potential for this simplified analytical model for near-real-time ET mapping from regional to continental scales.

Bhattarai, Nishan (ORCID:0000000327493549)↗