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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

C-Language Integrated Production System, Version 6.0

C Language Integrated Production System (CLIPS) computer programs are specifically intended to model human expertise or other knowledge. CLIPS is designed to enable research on, and development and delivery of, artificial intelligence on conventional computers. CLIPS 6.0 provides cohesive software tool for handling wide variety of knowledge with support for three different programming paradigms: rule-based, object-oriented, and procedural. Rule-based programming: representation of knowledge as heuristics - essentially, rules of thumb that specify set of actions performed in given situation. Object-oriented programming: modeling of complex systems comprised of modular components easily reused to model other systems or create new components. Procedural-programming: representation of knowledge in ways similar to those of such languages as C, Pascal, Ada, and LISP. Version of CLIPS 6.0 for IBM PC-compatible computers requires DOS v3.3 or later and/or Windows 3.1 or later.

Riley, Gary↗
NASA NTRS1989

A fast 3-D object recognition algorithm for the vision system of a special-purpose dexterous manipulator

A fast 3-D object recognition algorithm that can be used as a quick-look subsystem to the vision system for the Special-Purpose Dexterous Manipulator (SPDM) is described. Global features that can be easily computed from range data are used to characterize the images of a viewer-centered model of an object. This algorithm will speed up the processing by eliminating the low level processing whenever possible. It may identify the object, reject a set of bad data in the early stage, or create a better environment for a more powerful algorithm to carry the work further.

Hung, Stephen H. Y.↗
DOE OSTI2021

Root Influences on Mobilization and Export of Mineral-bound Soil Organic Matter

Biogeochemical cycles within mountainous watersheds are key regulators of ecosystem carbon storage and downstream nutrient loadings, and they have shown to be particularly vulnerable to climate change impacts. Increasing temperature and persistent droughts have already dramatically changed vegetation cover across the mountainous western US, with unknown consequences for soil carbon and nutrient cycles belowground. What remains elusive is to what extent associated changes in root-soil interactions may mobilize the vast pool of organic matter (OM) that has been stabilized by associations with minerals for centuries or millennia. Although plant root-driven OM mobilization from minerals may be a central control on carbon loss and nutrient export, such mechanisms are currently missing from conceptual and numerical models. The overall objective of this Exploratory Project is to identify the biogeochemical mechanisms by which roots destabilize mineral-associated organic matter (MAOM) and the cumulative impact on carbon and nutrient fate. To accomplish this goal, we integrated well-controlled laboratory experiments with in-field measurements and a scalable modeling approach. First, we conducted model system experiments to assess the vulnerability of MAOM to exudate-mediated mechanisms. Our results show that common root exudates effectively destabilize MAOM not only through direct, ligand-driven mobilization mechanisms, but also indirect, microbially-mediated mechanisms relying on secondary metabolites and enzymes. We further found that OM bound to poorly crystalline Fe and Al (hydr)oxides is more vulnerable to exudate-induced destabilization than OM bound to more crystalline phases, particularly in response to direct, ligand-promoted mechanisms. These findings demonstrate that the stability of MAOM is not just a function of their inherent properties, but also will depend in large parts on the ability of plant roots and microbes to produce exudates capable of triggering suitable mobilization mechanisms. We further employed a well-controlled rhizobox approach, combining advanced microsensor and mass spectrometry techniques, to resolve spatiotemporal variations in the composition and availability of exudates along single growing roots of grasses. Our results show that the composition of functionally relevant exudate compounds varies at extremely short time scales, seemingly shifting from ligands such as aromatic acids around root tips to less reactive metabolites such as amino acids around mature root segments. These results suggest a prevalence of direct MAOM mobilization mechanisms around the root tip, while indirect MAOM mobilization strategies may dominate around more mature root segments. Additionally, we utilized microsensor measurements in rhizoboxes to parameterize a rhizosphere (hydro)biogeochemistry reactive transport model (eSTOMP-ROOTS). The resulting model was used to assess how root exudations affects the stability of MAOM. Model simulations show that diel pulses of root exudation are strong enough to cause oscillations in biogeochemical conditions—particularly in pH, oxygen concentrations, and microbial activity— that repeatedly disrupt MAOM. Finally, we assessed field-scale impacts of root-driven MAOM destabilization over short and long time scales. A combination of in-field incubations and field-based characterizations showed that MAOM may not only be vulnerable to seasonal variations in root activity, but also to root-driven weathering over pedogenic time scales. In sum, results from our Exploratory Award highlight the strong control plant roots exert on MAOM mobilization and, thus, on the potential for carbon and nutrient export from watersheds.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1999

Integrated Modeling Tools for Thermal Analysis and Applications

Integrated modeling of spacecraft systems is a rapidly evolving area in which multidisciplinary models are developed to design and analyze spacecraft configurations. These models are especially important in the early design stages where rapid trades between subsystems can substantially impact design decisions. Integrated modeling is one of the cornerstones of two of NASA's planned missions in the Origins Program -- the Next Generation Space Telescope (NGST) and the Space Interferometry Mission (SIM). Common modeling tools for control design and opto-mechanical analysis have recently emerged and are becoming increasingly widely used. A discipline that has been somewhat less integrated, but is nevertheless of critical concern for high precision optical instruments, is thermal analysis and design. A major factor contributing to this mild estrangement is that the modeling philosophies and objectives for structural and thermal systems typically do not coincide. Consequently the tools that are used in these discplines suffer a degree of incompatibility, each having developed along their own evolutionary path. Although standard thermal tools have worked relatively well in the past. integration with other disciplines requires revisiting modeling assumptions and solution methods. Over the past several years we have been developing a MATLAB based integrated modeling tool called IMOS (Integrated Modeling of Optical Systems) which integrates many aspects of structural, optical, control and dynamical analysis disciplines. Recent efforts have included developing a thermal modeling and analysis capability, which is the subject of this article. Currently, the IMOS thermal suite contains steady state and transient heat equation solvers, and the ability to set up the linear conduction network from an IMOS finite element model. The IMOS code generates linear conduction elements associated with plates and beams/rods of the thermal network directly from the finite element structural model. Conductances for temperature varying materials are accommodated. This capability both streamlines the process of developing the thermal model from the finite element model, and also makes the structural and thermal models compatible in the sense that each structural node is associated with a thermal node. This is particularly useful when the purpose of the analysis is to predict structural deformations due to thermal loads. The steady state solver uses a restricted step size Newton method, and the transient solver is an adaptive step size implicit method applicable to general differential algebraic systems. Temperature dependent conductances and capacitances are accommodated by the solvers. In addition to discussing the modeling and solution methods. applications where the thermal modeling is "in the loop" with sensitivity analysis, optimization and optical performance drawn from our experiences with the Space Interferometry Mission (SIM), and the Next Generation Space Telescope (NGST) are presented.

Milman, Mark H.↗
NASA NTRS2025

CFD Validation of a Methanation Reactor With Cooling Jacket Used in an ISRU Propellant Production System

A digital model of an OxEon Energy methanation reactor (with a cooling jacket) planned for use in a NASA designed In-Situ Resource Utilization (ISRU) propellant production system was developed by the UTEP Aerospace Center using STAR-CCM+ software, a Siemens Computational Fluid Dynamics (CFD) package. The reactor digital model created includes two primary components: (i) a cooling jacket that maintains the required reactor chamber surface temperature and (ii) a reactor core chamber where the exothermic methanation reactions occur. The StarCCM+ digital model has two objectives: (i) maintain the surface temperature of the reactor below a set value so that the extra heat accumulation does not melt or crack the chamber, and (ii) produce the desired amount of methane (CH4) according to test cases completed by OxEon Energy for NASA JSC. The computational digital model was validated with the test data enabling the cooling jacket scale to be predicted based on the reactor's operating temperature. The StarCCM+ simulation of the digital model shows a good agreement with the cooling jacket performance and the CH4 production. One test case for the cooling jacket maintained the reactor wall temperature around 310 °C was validated and the reactor produced 185 g/hr CH 4 .

ISRU↗
DOE OSTI2018

Fracture Diagnostics Using Low Frequency Electromagnetic Induction and Electrically Conductive Proppants

The monitoring and diagnostics of induced fractures are important for the real-time performance evaluation of hydraulic fracturing operations. Previous electromagnetic (EM) based studies show that single backbone tri-axial induction logging tools are promising candidates for real-time monitoring and diagnosis of fractures in open-hole wells. To support the development of field deployable tools, the concept must be tested in experiments, in a controllable environment, before it is tested under field-like conditions. To this end, we have developed numerical tools which can simulate any wellbore environment while logging hydraulic fractures with the induction tool. We have designed and built a prototype induction tool and performed two sets of tests to compare with numerical simulation results. The computational and experimental setup consists of tri-axial transmitter- and receiver-coils in co-axial, co-planar and cross-polarized configurations. Both lab and shallow earth measurements are shown to be in good agreement with simulations for all examined cases. The average relative and maximum discrepancies of the measured signals from the simulated ones were lower than 3% and 10%, respectively. With the prototype tool, strong signals sensitive to the fracture’s surface area and dip-angle were measured in co-axial coil configuration, while weaker signals sensitive to the fracture’s aspect ratio were observed in the co-planar configuration. Cross-polarized signals are also shown to be strong and sensitive to the fracture’s dip. Lastly, we resolved the detectable components of the signal tensor to obtain parameters of simplified fracture geometries. The inversion algorithm, a derivative free directional search model, uses an objective function defined as a combination of co-axial and cross-polarized signals from different tool spacings to provide a well behaved global minimum. The robustness of inversion algorithm is tested on synthetic data for single cluster fractures in homogeneous and heterogeneous background electrical conductivity. All the effective model parameters for different cases, fracture conductivity (width), propped area (length) and dip-angle, are shown to be recovered with sufficient accuracy. We also evaluated the effect of multiple neighboring fractures and suggested a multi-cluster inversion algorithm that can accurately recover the proppant distribution in each fracture. Based on these results we provide a downhole tool design, with detailed specifications, that can effectively recover far-field proppant distribution in hydraulic fractures.

02 PETROLEUM↗
NASA NTRS1990

Exploration of unknown mechanical assemblies through manipulation

If robots must function in unstructured environments, they must also possess the ability to acquire information and construct appropriate models of the unknown environment. This paper addresses the automatic generation of kinematic models of unknown objects with movable parts in the environment. If the relative motion between moving parts must be observed and characterized, vision alone cannot suffice. An approach in which manipulation is used with vision for sensing is better suited to the task of determining kinematic properties. In this paper, algorithms for constructing models of unknown mechanical assemblies and characterizing the relative motion are developed. Results of a simulation are described to demonstrate the role of manipulation in such an endeavor.

Kumar, Vijay R.↗
DOE OSTI2019

Quantum Levitation of Fuel Capsules for Inertial Confinement Fusion

A major current challenge of the inertial confinement fusion (ICF) campaign is implosion perturbation due to fuel capsule support. Our current approach to hold ICF fuel capsules inside hohlraums is to sandwich a capsule between two thin polymeric films, referred to as tents. In addition to tents, variants of thin fibers have been used in some target designs to hold the capsule. Both tents and fibers cause strong implosion perturbations. An ideal solution to this problem is to hold the capsule inside the hohlraum by levitation, eliminating the perturbation-causing mechanical support. The goal of this project was to demonstrate a path to such an ideal capsule support solution based on quantum (superconducting) levitation. In our approach, the outer surface of the capsule is coated with a thin (about 100 nm) superconducting layer of MgB2, which is currently the most promising superconducting material candidate for this application. Magnetic coils outside the hohlraum are used to levitate and position the capsule in the center of the hohlraum. The scope of this project was limited to the first and arguably most critical step toward quantum levitation of ICF fuel capsules: the demonstration of thin-film superconductor coatings through a better understanding of the physics of defect- and interface-dominated superconducting behavior of ultrathin films. Specific objectives were (i) to develop a method for deposition of smooth and uniform thin films of MgB2 on ICF-scale spherical capsules; (ii) to better understand effects of film thickness, interfaces, and lattice defects on superconducting properties of MgB2; (iii) to perform cryogenic levitation experiments; and (iv) to develop a levitation model. All these objectives were met.

36 MATERIALS SCIENCE↗
NASA NTRS2000

Measurement Requirements for Improved Modeling of Arcjet Facility Flows

Current efforts to develop new reusable launch vehicles and to pursue low-cost robotic planetary missions have led to a renewed interest in understanding arc-jet flows. Part of this renewed interest is concerned with improving the understanding of arc-jet test results and the potential use of available computational-fluid- dynamic (CFD) codes to aid in this effort. These CFD codes have been extensively developed and tested for application to nonequilibrium, hypersonic flow modeling. It is envisioned, perhaps naively, that the application of these CFD codes to the simulation of arc-jet flows would serve two purposes: first. the codes would help to characterize the nonequilibrium nature of the arc-jet flows; and second. arc-jet experiments could potentially be used to validate the flow models. These two objectives are, to some extent, mutually exclusive. However, the purpose of the present discussion is to address what role CFD codes can play in the current arc-jet flow characterization effort, and whether or not the simulation of arc-jet facility tests can be used to eva1uate some of the modeling that is used to formu1ate these codes. This presentation is organized into several sections. In the introductory section, the development of large-scale, constricted-arc test facilities within NASA is reviewed, and the current state of flow diagnostics using conventional instrumentation is summarized. The motivation for using CFD to simulate arc-jet flows is addressed in the next section, and the basic requirements for CFD models that would be used for these simulations are briefly discussed. This section is followed by a more detailed description of experimental measurements that are needed to initiate credible simulations and to evaluate their fidelity in the different flow regions of an arc-jet facility. Observations from a recent combined computational and experiment.al investigation of shock-layer flows in a large-scale arc-jet facility are then used to illustrate the current state of development of diagnostic instrumentation, CFD simulations, and general knowledge in the field of arc-jet characterization. Finally, the main points are summarized and recommendations for future efforts are given.

Fletcher, Douglas G.↗
NASA NTRS1972

Payload analysis for space shuttle applications (study 2.2). Volume 3: Payload system operations analysis (task 2.2.1)

The technical and cost analysis that was performed for the payload system operations analysis is presented. The technical analysis consists of the operations for the payload/shuttle and payload/tug, and the spacecraft analysis which includes sortie, automated, and large observatory type payloads. The cost analysis includes the costing tradeoffs of the various payload design concepts and traffic models. The overall objectives of this effort were to identify payload design and operational concepts for the shuttle which will result in low cost design, and to examine the low cost design concepts to identify applicable design guidelines. The operations analysis examined several past and current NASA and DoD satellite programs to establish a shuttle operations model. From this model the analysis examined the payload/shuttle flow and determined facility concepts necessary for effective payload/shuttle ground operations. The study of the payload/tug operations was an examination of the various flight timelines for missions requiring the tug.

Source record↗
DOE OSTI2018

A parameterized ray-tracing model for evaluation of hemispherical lensing of a uniform, telecentric object aperture -- performance improvement estimates for segmented scintillators with miniature lens arrays

A parametric model describing the collimation of radiation from a uniform circular aperture by a hemispherical lens of the same radius has been developed for rapid estimation of the potential benefit of miniature dielectric lens arrays in lens-coupled gamma ray cameras (GRCs) with segmented scintillators. A simplified ray-tracing approach is adopted that makes use of small angle approximations relevant to GRCs used in nuclear science at Los Alamos National Laboratory and elsewhere. Application of this analysis technique in a first-pass design optimization process results in the optimistic estimate that miniature lenses fabricated from typical optical quality glass might boost optical coupling by as much as a factor of 4 (6 dB gain). However, this is not likely to be economically attractive compared to other techniques, such as reduction of the GRC lens f-number.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

TChem v2.0 - A Software Toolkit for the Analysis of Complex Kinetic Models

TChem is an open source software library for solving complex computational chemistry problems and analyzing detailed chemical kinetic models. The software provides support for: complex kinetic models for gas-phase and surface chemistry; thermodynamic properties based on NASA polynomials; species production/consumption rates; stable time integrator for solving stiff time ordinary differential equations; and, reactor models such as homogenous gas-phase ignition (with analytical Jacobian matrices), continuously stirred tank reactor, plug-flow reactor. This toolkit builds upon earlier versions that were written in C and featured tools for gas-phase chemistry only. The current version of the software was completely refactored in C++, uses an object-oriented programming model, and adopts Kokkos as its portability layer to make it ready for the next generation computing architectures i.e., multi/many core computing platforms with GPU accelerators. We have expanded the range of kinetic models to include surface chemistry and have added examples pertaining to Continuously Stirred Tank Reactors (CSTR) and Plug Flow Reactor (PFR) models to complement the homogenous ignition examples present in the earlier versions. To exploit the massive parallelism available from modern computing platforms, the current software interface is designed to evaluate samples in parallel, which enables large scale parametric studies, e.g. for sensitivity analysis and model calibration.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

A11I-2104 Evaluation of the NASA GEOS Chemistry-Climate Model Coupled Atmosphere-Ocean Configuration for its Suitability to Simulations of Atmospheric Composition in a Changing Climate

The NASA Goddard Earth Observing System Chemistry-Climate Model (GEOSCCM) is a full tropospheric-stratospheric chemistry enabled configuration of the NASA GEOS Earth system model. Among the objectives for research performed with GEOSCCM is to understand the impacts of climate change on recovery of the stratospheric ozone layer over the twenty-first century. Simulations performed in the past with GEOSCCM did not have an interactive ocean and were driven with projected sea surface temperature and sea ice boundary conditions provided by external models. This method limits the application of GEOSCCM for climate study because it doesn’t allow the feedback of composition changes to ocean. For a full representation of the chemistry-climate feedbacks in the Earth System, we have developed a configuration of GEOSCCM that makes use of the MOM5 ocean general circulation model coupled to the GEOS atmospheric general circulation model. This configuration leverages development of the GEOS Sub-seasonal-to-Seasonal (S2S) prediction system, and includes interactive, radiatively coupled aerosols and two-moment, aerosol-aware cloud microphysics. W e have assessed the baseline model climate sensitivity with an Monday, 11 December 2023 08:30 - 12:50 Poster Hall A-C - South (Exhibition Level, South, MC) experiment performed under pre-industrial (e.g., year 1850) greenhouse gas conditions and a second experiment under 4xCO2 conditions, similar to the typical CMIP protocol. The GEOS model is demonstrated to have a climate sensitivity of a 2.6 K increase in global mean surface temperature for an equivalent doubling of CO2 from pre-industrial conditions, in line with current CMIP models. This configuration of the GEOS model is suitable for application to multidecadal to century-long simulations of climate system response to changing greenhouse gas levels. We report here our evaluation of the climate diagnostics of this configuration and discuss future directions for work with this model configuration, including an ongoing twenty-first century projection experiment based on the Chemistry-Climate Model Intercomparison project protocol.

models↗
NASA NTRS1996

The Aggregate Representation of Terrestrial Land Covers Within Global Climate Models (GCM)

This project had four initial objectives: (1) to create a realistic coupled surface-atmosphere model to investigate the aggregate description of heterogeneous surfaces; (2) to develop a simple heuristic model of surface-atmosphere interactions; (3) using the above models, to test aggregation rules for a variety of realistic cover and meteorological conditions; and (4) to reconcile biosphere-atmosphere transfer scheme (BATS) land covers with those that can be recognized from space; Our progress in meeting these objectives can be summarized as follows. Objective 1: The first objective was achieved in the first year of the project by coupling the Biosphere-Atmosphere Transfer Scheme (BATS) with a proven two-dimensional model of the atmospheric boundary layer. The resulting model, BATS-ABL, is described in detail in a Masters thesis and reported in a paper in the Journal of Hydrology Objective 2: The potential value of the heuristic model was re-evaluated early in the project and a decision was made to focus subsequent research around modeling studies with the BATS-ABL model. The value of using such coupled surface-atmosphere models in this research area was further confirmed by the success of the Tucson Aggregation Workshop. Objective 3: There was excellent progress in using the BATS-ABL model to test aggregation rules for a variety of realistic covers. The foci of attention have been the site of the First International Satellite Land Surface Climatology Project Field Experiment (FIFE) in Kansas and one of the study sites of the Anglo-Brazilian Amazonian Climate Observational Study (ABRACOS) near the city of Manaus, Amazonas, Brazil. These two sites were selected because of the ready availability of relevant field data to validate and initiate the BATS-ABL model. The results of these tests are given in a Masters thesis, and reported in two papers. Objective 4: Progress far exceeded original expectations not only in reconciling BATS land covers with those that can be recognized from space, but also in then applying remotely-sensed land cover data to map aggregate values of BATS parameters for heterogeneous covers and interpreting these parameters in terms of surface-atmosphere exchanges.

Shuttleworth, W. James↗
NASA NTRS2012

Object-Oriented Bayesian Networks (OOBN) for Aviation Accident Modeling and Technology Portfolio Impact Assessment

The concern for reducing aviation safety risk is rising as the National Airspace System in the United States transforms to the Next Generation Air Transportation System (NextGen). The NASA Aviation Safety Program is committed to developing an effective aviation safety technology portfolio to meet the challenges of this transformation and to mitigate relevant safety risks. The paper focuses on the reasoning of selecting Object-Oriented Bayesian Networks (OOBN) as the technique and commercial software for the accident modeling and portfolio assessment. To illustrate the benefits of OOBN in a large and complex aviation accident model, the in-flight Loss-of-Control Accident Framework (LOCAF) constructed as an influence diagram is presented. An OOBN approach not only simplifies construction and maintenance of complex causal networks for the modelers, but also offers a well-organized hierarchical network that is easier for decision makers to exploit the model examining the effectiveness of risk mitigation strategies through technology insertions.

Shih, Ann T.↗
DOE OSTI2018

Defining Modeling and Analysis Complexity Needs for Remediation - 18425

Many subsurface remedy decisions rely on model predictions or other types of data analyses to support site characterization and remedy selection, design, implementation, performance assessment, and closure. Thus, determining the appropriate level of complexity for modeling and data analysis is important to facilitate subsurface remedy decisions. Multiple factors are important in selecting the appropriate level of complexity in modeling and data analysis. For instance, the type and number of inputs required typically increases with increased complexity of analysis, and the ability to obtain or verify those inputs needs to be considered. The approach needs to establish the relationship between parameters or processes and contaminant transport and the detail of the description needed to meet the analysis objectives. Assessing the modeling complexity associated with the appropriate level of detail can be facilitated by considering complexity of the 1) modeling approach, 2) description of process, and 3) description of heterogeneity. As demonstrated by case studies, using a framework to guide determination of modeling and analysis complexity facilitates selection of the appropriate approach for the site situation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Merging a mechanistic enzymatic model of soil heterotrophic respiration into an ecosystem model in two AmeriFlux sites of northeastern USA

Heterotrophic respiration (Rh), microbial processing of soil organic matter to carbon dioxide (CO 2 ), is a major, yet highly uncertain, carbon (C) flux from terrestrial systems to the atmosphere. Temperature sensitivity of Rh is often represented with a simple Q 10 function in ecosystem models and earth system models (ESMs), sometimes accompanied by an empirical soil moisture modifier. More explicit representation of the effects of soil moisture, substrate supply, and their interactions with temperature has been proposed as a way to disentangle the confounding factors of apparent temperature sensitivity of Rh and improve the performance of ecosystem models and ESMs. The objective of this work was to insert into an ecosystem model a more mechanistic, but still parsimonious, model of environmental factors controlling Rh and evaluate the model performance in terms of soil and ecosystem respiration. The Dual Arrhenius and Michaelis-Menten (DAMM) model simulates Rh using Michaelis-Menten, Arrhenius, and diffusion functions. Soil moisture affects Rh and its apparent temperature sensitivity in DAMM by regulating the diffusion of oxygen, soluble C substrates, and extracellular enzymes to the enzymatic reaction site. Here, we merged the DAMM soil flux model with a parsimonious ecosystem flux model, FöBAAR (Forest Biomass, Assimilation, Allocation and Respiration). We used high-frequency soil flux data from automated soil chambers and landscape-scale ecosystem fluxes from eddy covariance towers at two AmeriFlux sites (Harvard Forest, MA and Howland Forest, ME) in the northeastern USA to estimate parameters, validate the merged model, and to quantify the uncertainties in a multiple constraints approach. The optimized DAMM-FöBAAR model better captured the seasonal and inter-annual dynamics of soil respiration (Soil R) compared to the FöBAAR-only model for the Harvard Forest, where higher frequency and duration of drying events significantly regulate substrate supply to heterotrophs. However, DAMM-FöBAAR showed improvement over FöBAAR-only at the boreal transition Howland Forest only in unusually dry years. The frequency of synoptic-scale dry periods is lower at Howland, resulting in only brief water limitation of Rh in some years. At both sites, the declining trend of soil R during drying events was captured by the DAMM-FöBAAR model; however, model performance was also contingent on site conditions, climate, and the temporal scale of interest. While the DAMM functions require a few more parameters than a simple Q10 function, we have demonstrated that they can be included in an ecosystem model and reduce the model-data mismatch. Moreover, the mechanistic structure of the soil moisture effects using DAMM functions should be more generalizable than the wide variety of empirical functions that are commonly used, and these DAMM functions could be readily incorporated into other ecosystem models and ESMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A robust offering strategy for wind producers considering uncertainties of demand response and wind power

This paper proposes a risk-constrained decision-making approach for a wind power producer participating in the day-ahead market. In the developed model, a flexible demand response trading scheme between the wind power producer and different customers is employed. Through the proposed demand response mechanism, the wind power producer is able to trade demand response resource internally with different customers, and then trade energy externally with the market to increase the expected profit and the wind energy utilization. The uncertainties in the wind power and demand response are modeled by using the information gap decision theory approach from risk averse (robust) and risk-seeking (opportunistic) perspectives. The objective of the robust model is to maximize the robust level while satisfying the desired profit, whereas the opportunistic model aims to evaluate the possibility of achieving windfall profits with favorable uncertainties. The overall offering strategy problem is modeled as a bi-objective mixed integer nonlinear programming, which is linearized by proper techniques and solved efficiently by using the normal boundary intersection technique. In this work, simulation results show that utilizing demand response resource to mitigate wind power deviations can increase a wind power producer's profit and reduce potential risks. In addition, the results demonstrate that the proposed bi-objective optimization approach enables the wind power producer to select appropriate offering decisions with respect to uncertainties.

17 WIND ENERGY↗