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At least 199 records · Page 11

Model Formulations: Integrating Distributed Energy Resources (DER) using Advanced Unit Commitment Models and DER Aggregation Methodologies

A distribution energy resource aggregator (DERA) constitutes a group of distribution energy resources with small generation capacities which meet the threshold to participate in the electricity wholesale market. This document provides the proposed DERA model formulation that will be implemented in the SCUC simulation’s architecture for the SCUC-DER project. Different economical assessment methodologies have been developed to incorporated bids for individual distributed resources, which include solar cost dispatch and cost model, BESS opportunity cost offer algorithm, and price sensitive demand response model. Detailed methods are proposed to aggregate individual cost offers to a DERA cost curve to bid in SCUC market while three methods are proposed to simulate DER actual dispatch. Based on the DERA models in this document, the SCUC-DER project will be able to assess the impacts of DERA on the distribution system’s operation and reliability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Lambda-PFLOTRAN 1.0: a workflow for incorporating organic matter chemistry informed by ultra high resolution mass spectrometry into biogeochemical modeling

Abstract. Organic matter (OM) composition plays a central role in microbial respiration of dissolved organic matter and subsequent biogeochemical reactions. Here, a direct connection of organic matter chemistry and thermodynamics to reactive transport simulators has been achieved through the newly developed Lambda-PFLOTRAN workflow tool that succinctly incorporates carbon chemistry data generated from Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) into reaction networks to simulate organic matter degradation and the resulting biogeochemistry. Lambda-PFLOTRAN is a Python-based workflow, executed through a Jupyter notebook interface, that digests raw FTICR-MS data, develops a representative reaction network based on substrate-explicit thermodynamic modeling (also termed lambda modeling due to its key thermodynamic parameter λ used therein), and completes a biogeochemical simulation with the open source, reactive flow and transport code PFLOTRAN. The workflow consists of the following five steps: configuration, thermodynamic (lambda) analysis, sensitivity analysis, parameter estimation, and simulation output and visualization. Two test cases are provided to demonstrate the functionality of the Lambda-PFLOTRAN workflow. The first test case uses laboratory incubation data of temporal oxygen depletion to fit lambda parameters (i.e., maximum utilization rate and microbial carrying capacity). A slightly more complex second test case fits multiple lambda formulation and soil organic matter release parameters to temporal greenhouse gas generation measured during a soil incubation. Overall, the Lambda-PFLOTRAN workflow facilitates upscaling by using molecular-scale characterization to inform biogeochemical processes occurring at larger scales.

58 GEOSCIENCES↗

Nanolipoprotein particle (NLP) vaccine confers protection against Yersinia pestis aerosol challenge in a BALB/c mouse model

Introduction: Yersinia pestis is the etiological agent of plague, a disease that remains a concern as demonstrated by recent outbreaks in Madagascar. Infection with Y. pestis results in a rapidly progressing illness that can only be successfully treated with antibiotics given shortly after symptom onset. Live attenuated or whole cell inactivated vaccines confer protection against bubonic plague, but pneumonic plague has been more difficult to prevent. Novel effective subunit vaccine formulations may circumvent some of these shortfalls. Here, we compare the immunogenicity generated by an advanced subunit vaccine (F1V fusion protein) and a nanolipoprotein particle (NLP)-based vaccine. Methods: The NLP, a high-density lipoprotein mimetic, provides a nanoscale delivery platform for recombinant Y. pestis antigens LcrV (V) and F1. BALB/c mice were immunized via subcutaneous injection twice, three or four weeks apart. Four weeks later, splenocytes and sera were collected for immune profiling, and mice were challenged with aerosolized Y. pestis CO92. Results: Both formulations induced a strong IgG response against the F1 and V proteins, along with a robust memory B cell response and a balanced cell-mediated immune response as evidenced by both Th1- and Th2-related cytokines. The NLP-based vaccine induced a stronger cytokine response against F1, V, and F1V proteins relative to the F1V vaccine. As with F1V, the inclusion of Alhydrogel (Alu) in NLP vaccine formulations was critical for enhanced immunogenicity and protective efficacy. Mice that received two doses of F1:V:NLP + Alu and CpG were completely protected from a challenge with approximately eight median lethal doses of aerosolized Y. pestis CO92 and this protection confirmed the well-documented synergy between the F1 and V antigens in context of pneumonic plague. The NLPs have defined regions of polarity that facilitates the incorporation of a wide range of adjuvants and antigens with distinct physicochemical properties and are an excellent candidate platform for the development of multi-antigen vaccines.

F1↗

New results on the realizability of Reynolds stress turbulence closures

The realizability of Reynolds stress models in homogeneous turbulence is critically assessed from a theoretical standpoint. It is proven that a well known second-order closure formulated by Shih and Lumley using the strong realizability constraints of Schumann is, in fact, not a realizable model. The problem arises from the failure to properly satisfy the necessary positive second time derivative constraint when a principal Reynolds stress vanishes - a fatal flaw that becomes apparent when the non-analytic terms in their model are made single-valued as required on physical grounds. It is furthermore shown that the centrifugal acceleration generated by rotations of the principal axes of the Reynolds stress tensor can make the second derivative singular at the most extreme limits of realizable turbulence. This previously overlooked effect appears to make it impossible to identically satisfy the strong form of realizability in any version of the present generation of second-order closures. On the other hand, models properly formulated to satisfy the weak form of realizability - wherein states of one or two component turbulence are not accessible in finite time are found to be realizable. However, unlike the simpler and more commonly used second order closures, these models can be ill-behaved near the extreme limits of realizable turbulence due to the way that higher-degree nonlinearities are often unnecessarily introduced to satisfy realizability. Illustrative computations of homogeneous shear flows are presented to demonstrate these points which can have important implications for turbulence modeling.

Speziale, Charles G.↗

Transient flow analysis of the AEDC/HPDE MHD generator

A hybrid Lax-Wendroff/Method of Characteristics computer code has been developed for numerical simulation of flow transients associated with the operation of MHD generator facilities. The code employs the shock-fitting method, with an Eulerian formulation of the basic conservation equations and explicit tracking of shock waves. Pressure, temperature, and velocity are used as primary integration variables to simplify interfacing of the code with real-gas thermodynamic and transport property tables. Application of the code to the simulation of selected transients for the AEDC/HPDE MHD generator produced results that are in good agreement with experimental observations.

Wilson, D. R.↗

Cold Plasma Measurements

We have continued the simulation campaign in support of our ongoing magnetospheric cold plasma research project. This project aims to develop the next-generation particle instruments to measure the properties of the cold particle populations in the Earth’s magnetosphere. For this purpose, simulations have been performed with a Particle-In-Cell (PIC) code called the Curvilinear PIC (CPIC). The code is formulated in curvilinear geometry and couples the standard PIC algorithm with algorithms for the generation and adaptation of the underlaying computational mesh. It conforms to complex objects like spacecraft and it can place more grid points in regions where higher resolution is needed. The code also features a scalable solver based on the multigrid algorithm and it is fully parallelized via domain decomposition and MPI.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Multistage Stochastic optimization for mid-term integrated generation and maintenance scheduling of cascaded hydroelectric system with renewable energy uncertainty

The uncertainties resulting from the escalating penetration of renewable energy resources pose severe challenges to the efficient operation of modern power systems. Hydroelectricity is characterized by its flexibility, controllability, and reliability, and thus becomes one of the most ideal energy resources to hedge against such uncertainties. This paper studies the mid-term integrated generation and maintenance scheduling of a cascaded hydroelectric system (CHS) consisting of multiple cascaded reservoirs and hydroelectric units. To precisely describe the mid-term water regulation policies, the hydraulic coupling relationship and water-energy nexus of CHS are incorporated into the proposed optimization model. The uncertainties of natural water inflow and the power outputs of wind/solar energy generation are taken into consideration and captured via a stochastic process modeled by a scenario tree. A multistage stochastic optimization (MSO) approach is developed to coordinate the complementary operations of multiple energy resources, by optimizing the mid-term water resource management, generation scheduling, and maintenance scheduling of CHS. The proposed MSO model is formulated as a large-scale mixed-integer linear program that presents significant computational intractability. To address this issue, a tailored Benders decomposition algorithm is developed. Two real-world case studies are conducted to demonstrate the capability and characteristics of the proposed model and algorithm. The computational results show that the proposed MSO model can exploit the flexibility of hydroelectricity to efficiently respond to variable wind and solar power, and reserve water resources for the generation in peak months to reduce the consumption of fossil fuel. Furthermore, the proposed solution approach also exhibits promising computational efficiency when handling large-scale models.

13 HYDRO ENERGY↗

An Adaptively-Refined, Cartesian, Cell-Based Scheme for the Euler and Navier-Stokes Equations

A Cartesian, cell-based scheme for solving the Euler and Navier-Stokes equations in two dimensions is developed and tested. Grids about geometrically complicated bodies are generated automatically, by recursive subdivision of a single Cartesian cell encompassing the entire flow domain. Where the resulting cells intersect bodies, polygonal 'cut' cells are created. The geometry of the cut cells is computed using polygon-clipping algorithms. The grid is stored in a binary-tree data structure which provides a natural means of obtaining cell-to-cell connectivity and of carrying out solution-adaptive refinement. The Euler and Navier-Stokes equations are solved on the resulting grids using a finite-volume formulation. The convective terms are upwinded, with a limited linear reconstruction of the primitive variables used to provide input states to an approximate Riemann solver for computing the fluxes between neighboring cells. A multi-stage time-stepping scheme is used to reach a steady-state solution. Validation of the Euler solver with benchmark numerical and exact solutions is presented. An assessment of the accuracy of the approach is made by uniform and adaptive grid refinements for a steady, transonic, exact solution to the Euler equations. The error of the approach is directly compared to a structured solver formulation. A non smooth flow is also assessed for grid convergence, comparing uniform and adaptively refined results. Several formulations of the viscous terms are assessed analytically, both for accuracy and positivity. The two best formulations are used to compute adaptively refined solutions of the Navier-Stokes equations. These solutions are compared to each other, to experimental results and/or theory for a series of low and moderate Reynolds numbers flow fields. The most suitable viscous discretization is demonstrated for geometrically-complicated internal flows. For flows at high Reynolds numbers, both an altered grid-generation procedure and a different formulation of the viscous terms are shown to be necessary. A hybrid Cartesian/body-fitted grid generation approach is demonstrated. In addition, a grid-generation procedure based on body-aligned cell cutting coupled with a viscous stensil-construction procedure based on quadratic programming is presented.

Coirier, William John↗

Cloud-generated radiative heating and its generation of available potential energy

The generation of zonal available potential energy (APE) by cloud radiative heating is discussed. The APE concept was mathematically formulated by Lorenz (1955) as a measure of the maximum amount of total potential energy that is available for conversion by adiabatic processes to kinetic energy. The rate of change of APE is the rate of the generation of APE minus the rate of conversion between potential and kinetic energy. By radiative transfer calculations, a mean cloud-generated radiative heating for a well defined set of cloud classes is derived as a function of cloud optical thickness. The formulation is suitable for using a general cloud parameter data set and has the advantage of taking into account nonlinearities between the microphysical and macrophysical cloud properties and the related radiation field.

Stuhlmann, R.↗

Dispersive waves in a seeded MHD generator.

The equations giving the response of a slightly ionized plasma with monatomic components to sinusoidal perturbations have been formulated. Included in the model equations were the electron Hall effect, electron thermal diffusion, radiation, and electron-atom rate processes. Plasma conditions were limited to those where viscous effects, the induced magnetic field, ion slip, and atom-atom inelastic processes can be neglected. Presented are results of numerical calculations for MHD generators with a working fluid of potassium seeded argon.

Harstad, K. G.↗

Insulating Materials Comprising Polysilazane, Methods of Forming Such Insulating Materials, and Precursor Formulations Comprising Polysilazane

Methods of forming an insulating material comprising combining a polysilazane, a cross-linking compound, and a gas-generating compound to form a reaction mixture, and curing the reaction mixture to form a modified polysilazane. The gas-generating compound may be water, an alcohol, an amine, or combinations thereof. The cross-linking compound may be an isocyanate, an epoxy resin, or combinations thereof. The insulating material may include a matrix comprising one of a reaction product of a polysilazane and an isocyanate and a reaction product of a polysilazane and an epoxy resin. The matrix also comprises a plurality of interconnected pores produced from one of reaction of the polysilazane and the isocyanate and from reaction of the polysilazane and the epoxy resin. A precursor formulation that comprises a polysilazane, a cross-linking compound, and a gas-generating compound is also disclosed.

Larson, Robert S.↗

A Combined Geometric Approach for Computational Fluid Dynamics on Dynamic Grids

A combined geometric approach for computational fluid dynamics is presented for the analysis of unsteady flow about mechanisms in which its components are in moderate relative motion. For a CFD analysis, the total dynamics problem involves the dynamics of the aspects of geometry modeling, grid generation, and flow modeling. The interrelationships between these three aspects allow for a more natural formulation of the problem and the sharing of information which can be advantageous to the computation of the dynamics. The approach is applied to planar geometries with the use of an efficient multi-block, structured grid generation method to compute unsteady, two-dimensional and axisymmetric flow. The applications presented include the computation of the unsteady, inviscid flow about a hinged-flap with flap deflections and a high-speed inlet with centerbody motion as part of the unstart / restart operation.

Slater, John W.↗

NASA 2nd Generation RLV Program Introduction, Status and Future Plans

The Space Launch Initiative (SLI), managed by the Second Generation Reusable Launch Vehicle (2ndGen RLV) Program, was established to examine the possibility of revolutionizing space launch capabilities, define conceptual architectures, and concurrently identify the advanced technologies required to support a next-generation system. Initial Program funds have been allocated to design, evaluate, and formulate realistic plans leading to a 2nd Gen RLV full-scale development (FSD) decision by 2006. Program goals are to reduce both risk and cost for accessing the limitless opportunities afforded outside Earth's atmosphere fo civil, defense, and commercial enterprises. A 2nd Gen RLV architecture includes a reusable Earth-to-orbit launch vehicle, an on-orbit transport and return vehicle, ground and flight operations, mission planning, and both on-orbit and on-the-ground support infrastructures All segments of the architecture must advance in step with development of the RLV if a next-generation system is to be fully operational early next decade. However, experience shows that propulsion is the single largest contributor to unreliability during ascent, requires the largest expenditure of time for maintenance, and takes a long time to develop; therefore, propulsion is the key to meeting safety, reliability, and cost goals. For these reasons, propulsion is SLI's top technology investment area.

Dumbacher, Dan L.↗

A survey of nested grid techniques and their potential for use within the MASS weather prediction model

A survey of various one- and two-way interactive nested grid techniques used in hydrostatic numerical weather prediction models is presented and the advantages and disadvantages of each method are discussed. The techniques for specifying the lateral boundary conditions for each nested grid scheme are described in detail. Averaging and interpolation techniques used when applying the coarse mesh grid (CMG) and fine mesh grid (FMG) interface conditions during two-way nesting are discussed separately. The survey shows that errors are commonly generated at the boundary between the CMG and FMG due to boundary formulation or specification discrepancies. Methods used to control this noise include application of smoothers, enhanced diffusion, or damping-type time integration schemes to model variables. The results from this survey provide the information needed to decide which one-way and two-way nested grid schemes merit future testing with the Mesoscale Atmospheric Simulation System (MASS) model. An analytically specified baroclinic wave will be used to conduct systematic tests of the chosen schemes since this will allow for objective determination of the interfacial noise in the kind of meteorological setting for which MASS is designed. Sample diagnostic plots from initial tests using the analytic wave are presented to illustrate how the model-generated noise is ascertained. These plots will be used to compare the accuracy of the various nesting schemes when incorporated into the MASS model.

Koch, Steven E.↗

SatNet: A Benchmark for Satellite Scheduling Optimization

Satellites provide essential services such as networking and weather tracking, and the number of near-earth and deep space satellites are expected to grow rapidly in the coming years. Communications with terrestrial ground stations is one of the critical functionalities of any space mission. Satellite scheduling is a problem that has been scientifically investigated since the 1970s. A central aspect of this problem is the need to consider resource contention and satellite visibility constraints as they require line of sight. Due to the combinatorial nature of the problem, prior solutions such as linear programs and evolutionary algorithms require extensive compute capabilities to output a feasible schedule for each scenario. Machine learning based scheduling can provide an alternative solution by training a model with historical data and generating a schedule quickly with model inference. We present SatNet, a benchmark for satellite scheduling optimization based on historical data from the NASA Deep Space Network. We propose formulation of the satellite scheduling problem as a Markov Decision Process and use reinforcement learning (RL) policies to generate schedules. The nature of constraints imposed by SatNet differ from other combinatorial optimization problems such as vehicle routing studied in prior literature. Our initial results indicate that RL is an alternative optimization approach that can generate candidate solutions of comparable quality to existing state-of-the-practice results. However, we also find that RL policies overfit to the training dataset and do not generalize well to new data, thereby necessitating continued research on reusable and generalizable agents.

Wilson, Brian↗

Symbolic construction of the chemical Jacobian of quasi-steady state (QSS) chemistries for Exascale computing platforms

The Quasi-Steady State Approximation (QSSA) can be an effective tool for reducing the size and stiffness of chemical mechanisms for implementation in computational reacting flow solvers. However, for many applications, the resulting model still requires implicit methods for efficient time integration. Here, in this paper, we outline an approach to formulating the QSSA reduction that is coupled with a strategy to generate C++ source code to evaluate the net species production rates, and the chemical Jacobian. The code-generation component employs a symbolic approach enabling a simple and effective strategy to analytically compute the chemical Jacobian. For computational tractability, the symbolic approach needs to be paired with common subexpression elimination which can negatively affect memory usage. Several solutions are outlined and successfully tested on a 3D multipulse ignition problem, thus allowing portable application across chemical model sizes and GPU capabilities. The implementation of the proposed method is available at https://github.com/AMReX-Combustion/PelePhysics under an open-source license.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Lunar accelerometer network gravitational observatory (LANGO)

With ground-based interferometers detecting hundreds of gravitational-wave (GW) events, GW astronomy has continued to blossom. U.S. and European scientists are developing plans to construct third-generation ground-based interferometers. ESA has proceeded through the mission formulation phase of space-based interferometer in a lower-frequency band, 10 –4 –0.1 Hz. Despite all these exciting developments, there is still a missing frequency band, 0.1–10 Hz. This mid-frequency band is rich with interesting astrophysical events. Coalescence and merger of intermediate-mass black holes (IMBHs) will occur in this frequency band. Coalescing stellar-mass BHs will pass through this frequency band days before they reach the frequency band of LIGO and Virgo. Detection of such signals would enable a mid-frequency detector to issue an advance notice to the high-frequency GW detectors, as well as to optical, x-ray and γ-ray telescopes. We propose Lunar Accelerometer Network Gravitational Observatory (LANGO) to detect GWs in this frequency band. In the first phase (LANGO 1), we propose to deploy four ambient-temperature (250 K) accelerometers in the tetrahedral or in a square configuration on the hemisphere facing the Earth. After successful operation at 250 K, LANGO would be upgraded to a cryogenic (4 K) version with over two orders of magnitude increased sensitivity (LANGO 2), with coherent rejection of seismic noise implemented. LANGO is a full-tensor detector, capable of determining the source direction and wave polarization. Each test mass (TM) is suspended as a pendulum with resonance frequency ∼ 0.01 Hz, thus is only weakly coupled to the lunar surface horizontally. LANGO is designed to detect the relative motion of globally separated, nearly free, TMs by using the Moon as a large quiet platform. LANGO 1 and 2 accelerometers aim at sensitivities ⩽ 10 –11 m s –2 Hz –1/2 and ⩽ 10 –13 m s –2 Hz –1/2 in the horizontal axes over the frequency band of 1 mHz–10 Hz, which yield GW sensitivities 1.1 x 10 -21 Hz -1/2 and 3.8 x 10 -24 Hz -1/2 at 1 Hz, respectively. The LANGO accelerometers will be 10 3 –10 5 times more sensitive than Apollo seismometers. With such sensitivity, LANGO will also make great contribution to the advancement of lunar geophysics.

79 ASTRONOMY AND ASTROPHYSICS↗

Cubic spline functions for curve fitting

FORTRAN cubic spline routine mathematically fits curve through given ordered set of points so that fitted curve nearly approximates curve generated by passing infinite thin spline through set of points. Generalized formulation includes trigonometric, hyperbolic, and damped cubic spline fits of third order.

Young, J. D.↗