Requirements decomposition analysis
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Requirements decomposition analysis
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flowdown↗
Distributed Rules-Based Deconfliction of ADMS Applications: Part 1: Requirements & Decomposition
This work introduces a rules-based deconfliction methodology for resolving conflicting device control commands issued by advanced power applications considering a range of technical, economic, environmental, and social objectives. The methodology is designed to serve as one of multiple alternative implementations (along with application cooperation and global optimization) for the numerical component of the Deconfliction Pipeline. Development of the methodology is divided into two parts. This first document introduces the requirements, context, and methods for decomposing the deconfliction problem using the Laminar Coordination Framework and Variable Grid Structures. The deconfliction problem is decomposed into a distributed optimization problem based on the concept of quasi-static grid segments, which form independent distributed areas for control and coordination. Selection of the optimal number of decompositions of the deconfliction problem should be made based on a tradeoff analysis between computational speed and global optimality. This second document will define an initial set of technical, economic, and environmental criteria, as well as thirty specific qualitative rules that are used as part of the deconfliction methodology to eliminate non-viable setpoint alternatives. The deconfliction optimization problem is converted into a ranking of individual discrete setpoints, which are scored by the extent to which they satisfy specific decision criteria. The ranking is determined through the concepts of deconfliction exclusivity, priority, and preference. Several multi-criteria decision-making frameworks are examined with the simple multi-attribute rating technique exploiting ranks (SMARTER) recommended as a simple implementation alternative that aligns with the steps of the rules-based deconfliction methodology.
97 MATHEMATICS AND COMPUTING↗
Catalytic Site Requirements for N2O Decomposition on Cu-, Co-, and Fe-SSZ-13 Zeolites
N2O decomposition is investigated on Cu, Co and Fe-exchanged SSZ-13 zeolite catalysts at relatively low metal loadings. The catalysts are synthesized by solution ion exchange, and subjected to X-ray diffraction (XRD), temperature-programed-reduction by H2 (H2-TPR), temperature-programed-reaction of N2O (N2O-TPR) coupled with in-situ transmission FTIR, and finally steady-state flow reaction tests. At low N2O pressures (< 0.05 kPa), all catalysts display pseudo first-order kinetics. From Arrhenius analysis, Cu and Fe-SSZ-13 display very different apparent activation energies but similar pre-exponential factors, suggesting their similar reaction mechanisms. N2O decomposition follows a dual-site mechanism, occurring on dimeric M-O-M sites in these catalysts, and O2 is formed by the combination of two O ad-atoms from two vicinal metal sites. Under low N2O pressure (0.05 kPa) and first-order kinetic regime, the reaction is limited by N-O cleavage on bare metal active sites. In comparison to Cu-SSZ-13, the much higher N2O decomposition rate over Fe-SSZ-13 is attributed to the much lower activation barriers for the N-O cleavage step. N2O decomposition occurs on isolated Co2+ ions in Co-SSZ-13. The rate-limiting step is N-O cleavage on an O-occupied Co site in the low-pressure first order kinetic regime. This single-site mechanism leads to much higher pre-exponential factors as compared to the dual-site mechanism. This beneficial factor for reaction rate enhancement, however, is compromised by the much higher activation barriers over this catalyst.
Lin, Fan↗
SNoGloDe: A Structured Nonlinear Global Decomposition Solver
Large-scale optimization problems often require decomposition strategies and customized algorithms to achieve optimal solutions within a reasonable time. Building on the work of Cao and Zavala (2019) for solving nonlinear two-stage stochastic programs to global optimality, we implement and extend their approach. We generalize to optimization problems reformulated with a block-angular constraint structure (e.g., temporal decomposition). Our framework, written in Python using Pyomo, is highly customizable and enables parallel execution of the decomposition. SNoGloDe allows tailored branching strategies, lower bounding problems, and candidate generators to leverage problem-specific knowledge. To demonstrate effectiveness, we compare SNoGloDe’s performance with Gurobi on a temporally decomposed produced water case study.
algorithms↗
The chemical instability of Na{sub 2}IrO{sub 3} in air
Highlights: • Na{sub 2}IrO{sub 3} decomposes rapidly in laboratory air. • The decomposition requires the simultaneous presence of CO{sub 2} and H{sub 2}O. • Decomposition results in a dramatic change in the magnetic properties. • Second 5 K feature in magnetic susceptibility not previously reported. - Abstract: We report that Na{sub 2}IrO{sub 3}, which has a layered honeycomb iridium oxide sublattice interleaved by Na planes, decomposes in laboratory air while maintaining the same basic crystal structure. The decomposition reaction was monitored by time-dependent powder X-ray diffraction under different ambient atmospheres, through which it was determined that it occurs only in the simultaneous presence of both CO{sub 2} and H{sub 2}O. A hydrated sodium carbonate is the primary decomposition product along with altered Na{sub 2}IrO{sub 3}. The diffraction signature of the altered Na{sub 2}IrO{sub 3} is quite similar to that of the pristine material, which makes the detection of decomposition difficult in a sample handled under ordinary laboratory conditions. The decomposed samples show a significantly decreased magnetic susceptibility and the disappearance of the low temperature antiferromagnetic transition considered to be characteristic of the phase. Samples that have never been exposed to air after synthesis display a previously unreported magnetic transition at 5 K.
36 MATERIALS SCIENCE↗
On computing stress in polymer systems involving multi-body potentials from molecular dynamics simulation
Hardy stress definition has been restricted to pair potentials and embedded-atom method potentials due to the basic assumptions in the derivation of a symmetric microscopic stress tensor. Force decomposition required in the Hardy stress expression becomes obscure for multi-body potentials. In this work, we demonstrate the invariance of the Hardy stress expression for a polymer system modeled with multi-body interatomic potentials including up to four atoms interaction, by applying central force decomposition of the atomic force. The balance of momentum has been demonstrated to be valid theoretically and tested under various numerical simulation conditions. The validity of momentum conservation justifies the extension of Hardy stress expression to multi-body potential systems. Computed Hardy stress has been observed to converge to the virial stress of the system with increasing spatial averaging volume. This work provides a feasible and reliable linkage between the atomistic and continuum scales for multi-body potential systems.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
3D And 4D Cloud Lifecycle Investigations Using Innovative Scanning Radar Analysis Methods. Final report
With the vast upgrades to the ARM program radar measurement capabilities in 2010 and beyond, our ability to probe the 3D structure of clouds and associated precipitation has increased dramatically. This project build on the PI's and co-I's expertisein the analysis of radar observations. The first research thrust aims to document the 3D morphological (as depicted by the radar reflectivity structure) and 3D dynamical (cloud$-$scale eddies) structure of boundary layer clouds. Unraveling the 3D dynamical structure of stratocumulus and shallow cumulus clouds requires decomposition of the environmental wind contribution and particle sedimentation velocity from the observed radial Doppler velocity. The second thrust proposes to unravel the mechanism of cumulus entrainment (location, scales) and its impact on microphysics utilizing radar measurements from the vertically pointing and new scanning radars at the ARM sites. The third research thrust requires the development of a cloud$-$tracking algorithm that monitors the properties of cloud.
3D structure↗
Reliability-Aware Requirements Development for Autonomy Software
Autonomy is the ability of a system to make decisions and take actions in the presence of uncertainty. Validating autonomy, therefore, is a matter of validating that the system makes intelligent decisions even when there might be discrepancies between the observed and the expected state of the world as well as when the possible outcome of each of the possible courses of action is uncertain. During the requirements engineering phase, the functions, including those that are required to be autonomous and their expected behavior are specified. However, in the case of autonomous software system, it is challenging to specify all possible scenarios that the software may encounter. Additionally, since autonomous behaviors cannot always be fully predetermined, it is difficult to reason about their completeness and correctness. While these challenges are also faced with non-autonomous system, they are more prevalent for autonomous system due to their complexity and emergent behavior. Our efforts have been three-fold. On one hand, we have developed a goal-based method for requirements decomposition. We have embedded this approach into a higher-level systems engineering framework and then developed methods for decision and reliability analysis within this framework. And finally, we use simulation analysis to validate the more theoretical methods and provide a feedback mechanism. The decision analysis approach (DA) helps in identifying and mitigating the run-time risks, by bringing to the forefront the uncertainties, decisions, interactions, and other factors that may cause autonomous software to make erroneous decisions. The DA framework is used to quantify, for each decision that the software can make, failure risk due to uncertainties. The information about the key decisions and circumstances that can cause autonomous system to make incorrect decisions are used to generate test scenarios to be run in a simulator to ensure that the system can handle error-prone circumstances. The results or outcomes from decisions, based on the simulated scenarios, can then be leveraged to further gain insight of the assured system. We combine a goal-based approach with simulation analysis to facilitate requirements development for autonomous systems and further provide a method for run-time systems level reliability considerations during the autonomous software development process. The DA and the reliability analysis methods provide a formalism for the consideration of uncertainty in the run time decision-making process for autonomous software. This formalism considers the uncertainty involved in the outcome of different courses of action, in terms of performance and cost, as well as a method to consider the system level reliability implications. System level reliability considerations for autonomous software decision making contribute to the satisfaction of the system level goals over the lifecycle of a given mission. We demonstrate our approach using a hypothetical rover path planning example. The requirements for our rover simulator are based on existing literature about Mars rovers and lessons learned from real world observations at JPL. The specifics of the autonomy design for the Mars rovers, that have not been previously cleared for external release, are not used for our demonstrations.
Lindvall, Mikael↗
An efficient design sensitivity analysis of eigenvectors
Subspace iteration has been a major advance in solving large eigen problems when only a subset of eigen-pairs is required. The essence of this method is a transformation from displacement coordinates of an n-th order eigensystem to generalized coordinates of a smaller q-th order. The eigenvalue problem is then solved in the reduced space. The method was first developed by Clint and Jennings for real symmetric systems and was then called 'simultaneous iteration'. The success of the method prompted further research along this line and there have been many improved algorithms developed. This approach has been widely used by structural engineers for extracting the most useful natural frequencies and mode shapes of large-scale dynamic systems. This paper exploits into a new direction which is in the form of iterative process for simultaneously calculating eigenvector derivatives of many eigenvectors with respect to multi-variables. The method fully uses all the available information from preceding eigenvalue solution and, thus, effectively economizes computational efforts. It iterates through two equations derived from the first variation of the two fundamental equations used in subspace iteration method. There is no expensive large matrix decomposition required and the process converges to acceptable solution in a finite number of iterations. Therefore, the procedure increases its efficiency superiority over the others as the system size or the number of interested eigenvectors become larger and larger.
Ting, T.↗
Modeling Interactive Effects of Manganese Bioavailability, Nitrogen Deposition, and Warming on Soil Carbon Storage
Manganese (Mn) is a redox–active micronutrient that has been shown to accelerate plant litter decomposition; however, the effect of Mn–promoted decomposition on soil C storage is unclear. We present a novel biogeochemical model simulating how Mn bioavailability influences soil organic C (SOC) stocks in a soil profile (<50 cm) within a temperate forest. In our model, foliar Mn increased in response to increasing soluble Mn released through Mn–oxide (birnessite) dissolution in mineral soil layers. The ensuing Mn enrichment in leaf litter redistributed Mn to the surface forest floor layer, promoted enzymatic oxidation of lignin, and decreased SOC stocks. Total SOC loss was partially mitigated by accumulation of lignin–oxidation products as mineral–associated organic C. We also explored how Mn–driven changes to C storage interacted with effects of N deposition and warming. Nitrogen enrichment inhibited Mn–dependent lignin degradation, increasing SOC stocks and weakening their dependence on Mn bioavailability. Warming stimulated decomposition and reduced C stocks but was less effective at low Mn bioavailability. Our model results suggest that SOC stocks are sensitive to Mn bioavailability because increased plant uptake redistributes Mn to surface soils where it can enhance litter decomposition. Finally, based on our simulations, we predict that Mn becomes limiting to litter decomposition where Mn is poorly soluble. Depletion of bioavailable Mn or other cofactors that are critical to decomposition could limit the response of organic C stocks to warming over time, but quantitative projections of the role of Mn bioavailability in regulating decomposition requires additional measurements to constrain model uncertainties.
58 GEOSCIENCES↗
Exploring redshift-space distortions in large-scale structure
We explore and compare different ways large-scale structure observables in redshift-space and real space can be connected. These include direct computation in Lagrangian space, moment expansions and two formulations of the streaming model. Here we derive for the first time a Fourier space version of the streaming model, which yields an algebraic relation between the real- and redshift-space power spectra which can be compared to earlier, phenomenological models. By considering the redshift-space 2-point function in both configuration and Fourier space, we show how to generalize the Gaussian streaming model to higher orders in a systematic and computationally tractable way. We present a closed-form solution to the Zeldovich power spectrum in redshift space and use this as a framework for exploring convergence properties of different expansion approaches. While we use the Zeldovich approximation to illustrate these results, much of the formalism and many of the relations we derive hold beyond perturbation theory, and could be used with ingredients measured from N-body simulations or in other areas requiring decomposition of Cartesian tensors times plane waves. Lastly, we finish with a discussion of the redshift-space bispectrum, bias and stochasticity and terms in Lagrangian perturbation theory up to 1-loop order.
79 ASTRONOMY AND ASTROPHYSICS↗
Drag and Lift Forces Between a Rotating Conductive Sphere and a Cylindrical Magnet
Modeling the interaction between a non-uniform magnetic field and a rotating conductive object allows study of the drag force which is used in applications such as eddy current braking and linear induction motors as well as the transition to a repulsive force that is the basis for magnetic levitation systems. Here, we study the interaction between a non-uniform field generated by a cylindrical magnet and a rotating conductive sphere. Each eddy current in the sphere generates a magnetic field which in turn generates another eddy current, eventually feeding back on itself. A two step mathematics process is developed to find a closed form solution in terms of only two eddy currents. However, the complete solution requires decomposition of the magnetic field into a summation of spherical harmonics, making it more suitable for a graduate level electromagnetism lecture or lab. Finally, the forces associated with these currents are calculated and then verified experimentally.
Nurge, Mark A.↗
Balancing conflicting requirements for grid and particle decomposition in continuum-Lagrangian solvers
Not Available
Sitaraman, Hariswaran↗
Human Systems Integration: Requirements and Functional Decomposition
This deliverable was intended as an input to the Access 5 Policy and Simulation Integrated Product Teams. This document contains high-level pilot functionality for operations in the National Airspace System above FL430. Based on the derived pilot functions the associated pilot information and control requirements are given.
Berson, Barry↗
A new algorithm for the integration of exponential and logarithmic functions
An algorithm for symbolic integration of functions built up from the rational functions by repeatedly applying either the exponential or logarithm functions is discussed. This algorithm does not require polynomial factorization nor partial fraction decomposition and requires solutions of linear systems with only a small number of unknowns. It is proven that if this algorithm is applied to rational functions over the integers, a computing time bound for the algorithm can be obtained which is a polynomial in a bound on the integer length of the coefficients, and in the degrees of the numerator and denominator of the rational function involved.
Rothstein, M.↗
Permeable Membrane Reactor for Ammonia Decomposition - RUPS
The generation of impurities in gas processing facilities must be counteracted to minimize downstream impacts to process components and piping. Reservoir Unloading Purification System (RUPS) is an umbrella term describing research and development activities to remove impurities from current and future facility gases. As the application of developed RUPS technologies matures, the technologies will be verified in the Hydrogen Processing Demonstration System (HPDS) to provide a holistic view of the process before future implementation. By adding catalyst, it is possible to decrease the activation energy typically required for decomposition of ammonia. This allows a drastic decrease in required temperatures necessary for the reaction to take place in a permeable membrane reactor (PMR) (from > 650 deg. C to < 425 deg. C). A PMR was fabricated for scoping studies. The primary objective of this research is to determine whether the use of a PMR containing ruthenium catalyst can provide a favorable environment for maximum ammonia decomposition at moderate temperatures. Scoping studies will be performed to determine the catalytic capability of Ru-Al{sub 2}O{sub 3} or Ru-SiO{sub 2} to determine the effectiveness of ammonia decomposition with a PMR. Tests will evaluate effects of: gas composition/impurity concentration, catalyst loading, test cell space velocity, and various carrier gases of interest.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Interaction of light with the ZnO surface: Photon induced oxygen “breathing,” oxygen vacancies, persistent photoconductivity, and persistent photovoltage
ZnO surfaces adsorb oxygen in the dark and emit CO{sub 2} when exposed to white light, reminiscent of the lungs of living creatures. We find that this exchange of oxygen with the ambient affects the integrity of the ZnO surface. Thus, it forms a basis for several interesting surface phenomena in ZnO, such as photoconductivity, photovoltage, and gas sensing, and has a role in ZnO electrical conduction. Using x-ray photoelectron spectroscopy on ZnO nanowires, we observed a decomposition of ZnO under white light and formation of oxygen-depleted surface, which explains photoconductivity by the electron donation of oxygen vacancies. Our findings suggest that the observed decomposition of the ZnO lattice may only take place due to photon-induced reduction of ZnO by carbon containing molecules (or carbo-photonic reduction), possibly from the ambient gas, accounting in a consistent way for both the reduced demands on the energy required for decomposition and for the observed emission of lattice oxygen in the form of CO{sub 2}. The formation of oxygen-vacancy rich surface is suggested to induce surface delta doping, causing accumulation of electrons at the surface, which accounts for both the increase in conductivity and the flattening of the energy bands. Using surface photovoltage spectroscopy in ultra high vacuum, we monitored changes in the deep level spectrum. We observe a wide optical transition from a deep acceptor to the conduction band, which energy position coincides with the position of the so called “green luminescence” in ZnO. This green transition disappears with the formation of surface oxygen vacancies. Since the oxygen vacancies are donors, while the green transition involves surface acceptors, the results suggest that the initial emission of oxygen originates at the defect sites of the latter, thereby eliminating each other. This suggests that the green transition originates at surface Zn vacancy acceptors. Removing an oxygen atom from a Zn vacancy completes the vacancy to become a full ZnO molecule vacancy, which does not produce deep levels. Our results explain why ZnO finds use as an electrical detector for oxygen and for carbon containing gas molecules. They may also shed new light on photocatalytic uses of ZnO. It is suggested that similar surface phenomena may affect other semiconducting oxides.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗