MINLP formulation and solution strategies for network- constrained unit commitment with nonlinear AC models.
Abstract not provided.
Laird, Carl Damon↗
SEARCH · Engineering Papers
Results for “network solutions”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Simulation of solute transport through heterogeneous networks: analysis using the method of moments and the statistics of local transport characteristics
We used a time domain random walk approach to simulate passive solute transport in networks. In individual pores, solute transport was modeled as a combination of Poiseuille flow and Taylor dispersion. The solute plume data were interpreted via the method of moments. Analysis of the first and second moments showed that the longitudinal dispersivity increased with increasing coefficient of variation of the pore radii CV and decreasing pore coordination number Z. The third moment was negative and its magnitude grew linearly with time, meaning that the simulated dispersion was intrinsically non-Fickian. The statistics of the Eulerian mean fluid velocities $\hat{u}_i$, the Taylor dispersion coefficients $\hat{D}_i$ and the transit times $\hat{t}_i$ were very complex and strongly affected by CV and Z. In particular, the probability of occurrence of negative velocities grew with increasing CV and decreasing Z. Hence, backward and forward transit times had to be distinguished. The high-τ branch of the transit-times probability curves had a power law form associated to non-Fickian behavior. However, the exponent was insensitive to pore connectivity, although variations of Z affected the third moment growth. Thus, we conclude that both the low- and high-τ branches played a role in generating the observed non-Fickian behavior.
Li, Min↗
Size-exclusion partitioning of neutral solutes in crosslinked polymer networks: A Monte Carlo simulation study
In this work, the size-exclusion partitioning of neutral solutes in crosslinked polymer networks has been studied through Monte Carlo simulations. Two models that provide user-friendly expressions to predict the partition coefficient have been tested over a wide range of volume fractions: Ogston's model (especially devised for fibrous media) and the pore model. The effects of crosslinking and bond stiffness have also been analyzed. Our results suggest that the fiber model can acceptably account for size-exclusion effects in crosslinked gels. Its predictions are good for large solutes if the fiber diameter is assumed to be the effective monomer diameter. For solutes sizes comparable to the monomer dimensions, a smaller fiber diameter must be used. Regarding the pore model, the partition coefficient is poorly predicted when the pore diameter is estimated as the distance between adjacent crosslinker molecules. On the other hand, our results prove that the pore sizes obtained from the pore model by fitting partitioning data of swollen gels are overestimated.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Regression-Based Analytics for Response Dynamics of SDN Solutions and Components
We consider Software-Defined Network (SDN) solutions that dynamically setup and teardown connections, and also their response dynamics of connectivity and TCP throughput. There is a wide variety of choices for controllers, switches, andsoftware modules, and objective analytics of measurements are needed to compare the response dynamics of solutions based on their combinations. Throughput and ping measurements during connection changes contain significant statistical variations due to the complexities of controllers, northbound scripts, and network devices. We propose analytical methods to estimate response regression functions, which provide a rigorous and objective comparison of different SDN solutions and their components, namely, controllers, switches, and OpenFlow versions. We apply this approach in two scenarios: (a) switching of long-haul connections emulated in hardware by ANUE devices over a testbed consisting of HP and Cisco switches, and (b) multi-site science infrastructure emulated using VMs and Mininet. The results provide useful practical insights including: (i) the dpctl method responds seconds faster than the OpenDayLight (ODL) method on average under OpenFlow 1.0, but performs similar to ODL under OpenFlow 1.3, and (ii) the ping response of dpctl is about 0.6 sec faster than ODL for the second scenario.
97 MATHEMATICS AND COMPUTING↗
Characterizing the Impacts of Multi-Scale Heterogeneity on Solute Transport in Fracture Networks
We model flow and transport in fracture networks with varying degrees of fracture-to-fracture aperture heterogeneity and network intensity to show how changes in these properties can cause the emergence of anomalous flow and transport behavior. If fracture-to-fracture aperture heterogeneity is increased in sparse networks, velocity fluctuations inhibit high flow rates and solute transport can be delayed. Surprisingly, transport can be slowed even in cases where hydraulic aperture is monotonically increased. As the intensity of the networks is increased, more connected pathways allow for particles to bypass these effects. There exists transition behavior where with relatively few connected pathways in a network, first arrival times of particles are not heavily affected by fracture-to-fracture aperture heterogeneity, but the scaling behavior of the tails is strongly influenced. These results reinforce the importance of considering multi-scale effects in fractured systems and can inform flow and transport processes in both natural and engineered fractured systems.
58 GEOSCIENCES↗
A Scalable Solution Route to Porous Networks of Nanostructured Black Tungsten
This paper studied the feasibility of a new solution-processed method to manufacture black tungsten nanostructures by laser conversion of tungsten hexacarbonyl precursor on the Inconel 625 substrate under argon atmosphere at ambient pressure. The results show that sublimation of the precursor can be prevented if the decomposition temperature (>170 °C) is achieved using the laser heating method. Three different laser powers from 60–400 W were used to investigate the role of laser parameters on the conversion. It was found that lower laser power of 60 W resulted in a mixture of unconverted precursor and converted tungsten. Higher laser powers >200 W resulted in α-W (BCC) in one step without further heat treatment. Different oxygen concentrations from 0.5 ppm to 21 vol% were used in the laser canister to investigate the effect of oxygen concentration on the conversion. It was found that the hard vacuum (>10−4 torr) or hydrogen is not necessary to obtain α-W (BCC). The solar absorptance varied from 63–97%, depending on the amount of precursor deposited on the substrate and oxygen content in the laser canister. This solution-based laser conversion of tungsten precursor is a scalable method to manufacture tungsten coatings for high-temperature applications.
14 SOLAR ENERGY↗
Learning and discovering multiple solutions using physics-informed neural networks with random initialization and deep ensemble
In this work we explore the capability of physics-informed neural networks (PINNs) to discover multiple solutions. Many real-world phenomena governed by nonlinear differential equations (DEs), such as fluid flow, exhibit multiple solutions under the same conditions, yet capturing this solution multiplicity remains a significant challenge. A key difficulty lies in providing appropriate initial conditions or guesses, as widely used time-marching schemes and Newton’s method are highly sensitive to these choices when solving complex computational problems. While machine learning models, particularly PINNs, have shown promise in solving DEs, their ability to capture multiple solutions remains underexplored. In this work, we propose a simple and practical approach using PINNs to learn and discover multiple solutions. We first demonstrate that PINNs, when combined with random initialization and deep ensemble method—originally developed for uncertainty quantification—can effectively uncover multiple solutions to nonlinear ordinary and partial DEs. Although training large ensembles of PINNs may appear computationally demanding, this can be done efficiently using vectorization techniques supported by modern deep learning frameworks, allowing many networks to be trained simultaneously. Our approach highlights the critical role of initialization in shaping solution diversity, addressing an often-overlooked aspect of machine learning for scientific computing. Furthermore, we propose utilizing PINN-generated solutions as initial conditions or initial guesses for conventional numerical solvers to enhance accuracy and efficiency in capturing multiple solutions. Extensive numerical experiments, including the Allen–Cahn equation and cavity flow, where our approach successfully identifies both stable and unstable solutions, validate the effectiveness of our method. These findings establish a general and efficient framework for addressing solution multiplicity in nonlinear DEs.
97 MATHEMATICS AND COMPUTING↗
Topological solution of bilateral switching networks
Topological method uses the eye as pattern detector to trace path of transmission on truth table. Pathway selection is continually supervised by logician, allowing him to seek planar iterative solution desirable for fabrication of monolithic circuits. Method applies to parity generators, multiple output functions, full adders, and bit comparators.
Mazer, L.↗
Using Swarming Agents for Scalable Security in Large Network Environments
The difficulty of securing computer infrastructures increases as they grow in size and complexity. Network-based security solutions such as IDS and firewalls cannot scale because of exponentially increasing computational costs inherent in detecting the rapidly growing number of threat signatures. Hostbased solutions like virus scanners and IDS suffer similar issues, and these are compounded when enterprises try to monitor these in a centralized manner. Swarm-based autonomous agent systems like digital ants and artificial immune systems can provide a scalable security solution for large network environments. The digital ants approach offers a biologically inspired design where each ant in the virtual colony can detect atoms of evidence that may help identify a possible threat. By assembling the atomic evidences from different ant types the colony may detect the threat. This decentralized approach can require, on average, fewer computational resources than traditional centralized solutions; however there are limits to its scalability. This paper describes how dividing a large infrastructure into smaller managed enclaves allows the digital ant framework to effectively operate in larger environments. Experimental results will show that using smaller enclaves allows for more consistent distribution of agents and results in faster response times.
agents↗
Countercations Control Local Specific Bonding Interactions and Nucleation Mechanisms in Concentrated Water-in-Salt Solutions
One of the continuing challenges presented in aqueous salt solutions is to understand ion association reactions driving dynamic demixing from solvation, complexation and solute clustering. The problems understanding this phenomenon are exacerbated in the highly-concentrated water-in-salt electrolytes, where the deficiency of water leads to a dramatic retardation of solvating water and formation of extended solvent-solute clustering networks. By probing microscopic dynamics of water and prenucleation clusters using quasi-elastic neutron scattering and proton nuclear magnetic resonance spectroscopy, we observed contrasting mechanistic specifics of ion-water mobilities in highly-concentrated Na+- vs. K+-based aluminate solutions (diffusion coefficients of 0.2 vs. 2.6?10-10m2s-1 at 293 K, respectively). The magnitude of the differences is far beyond the kosmotropic (Na+) and chaotropic (K+) effects typically understood at low ionic concentrations. The distinct crystallization mechanisms observed in analogous deuterated systems further imply that different prenucleation cluster dynamics and network packing morphologies can either frustrate or promote crystallization, as described by non-classical nucleation theory.
Wang, Hsiu-Wen↗
On the Existence of Steady-State Solutions to the Equations Governing Fluid Flow in Networks
The steady-state solution of fluid flow in pipeline infrastructure networks driven by junction/node potentials is a crucial ingredient in various decision-support tools for system design and operation. While the nonlinear system is known to have a unique solution (when one exists), the absence of a definite result on the existence of solutions hobbles the development of computational algorithms, for it is not possible to distinguish between algorithm failure and non-existence of a solution. In this letter, we show that for any fluid whose equation of state is a scaled monomial, a unique solution exists for such nonlinear systems if the term solution is interpreted in terms of potentials and flows rather than pressures and flows. However, for gases following the CNGA equation of state, while the question of existence remains open, we construct an alternative system that always has a unique solution and show that the solution to this system is a good approximant of the true solution. Further, the existence result for flow of natural gas in networks also applies to other fluid flow networks such as water distribution networks or networks that transport carbon dioxide in carbon capture and sequestration. Most importantly, our result enables correct diagnosis of algorithmic failure, problem stiffness, and non-convergence in computational algorithms.
42 ENGINEERING↗
Photonic and Opto-Electronic Applications of Polydiacetylene Films Photodeposited from Solution and Polydiacetylene Copolymer Networks
Polydiacetylenes (PDAS) are attractive materials for both electronic and photonic applications because of their highly conjugated electronic structures. They have been investigated for applications as both one-dimensional (linear chain) conductors and nonlinear optical (NLO) materials. One of the chief limitations to the use of PDAs has been the inability to readily process them into useful forms such as films and fibers. In our laboratory we have developed a novel process for obtaining amorphous films of a PDA derived from 2-methyl4-nitroaniline using photodeposition with Ultraviolet (UV) light from monomer solutions onto transparent substrates. Photodeposition from solution provides a simple technique for obtaining PDA films in any desired pattern with good optical quality. This technique has been used to produce PDA films that show potential for optical applications such as holographic memory storage and optical limiting, as well as third-order NLO applications such as all-optical refractive index modulation, phase modulation and switching. Additionally, copolymerization of diacetylenes with other monomers such as methacrylates provides a means to obtain materials with good processibility. Such copolymers can be spin cast to form films, or drawn by either melt or solution extrusion into fibers. These films or fibers can then be irradiated with UV to photopolymerize the diacetylene units to form a highly stable cross-linked PDA-copolymer network. If such films are electrically poled while being irradiated, they can achieve the asymmetry necessary for second-order NLO applications such as electro-optic switching. On Earth, formation of PDAs by the above mentioned techniques suffers from defects and inhomogeneities caused by convective flows that can arise during processing. By studying the formation of these materials in the reduced-convection, diffusion-controlled environment of space we hope to better understand the factors that affect their processing, and thereby, their nature and properties. Ultimately it may even be feasible to conduct space processing of PDAs for technological applications.
Paley, Mark S.↗
Global Solution Strategies for the Network-Constrained Unit Commitment Problem with AC Transmission Constraints
Here, we propose a novel global solution algorithm for the network-constrained unit commitment problem that incorporates a nonlinear alternating current (AC) model of the transmission network, which is a nonconvex mixed-integer nonlinear programming (MINLP) problem. Our algorithm is based on the multi-tree global optimization methodology, which iterates between a mixed-integer lower-bounding problem and a nonlinear upper-bounding problem. We exploit the mathematical structure of the unit commitment problem with AC power flow constraints (UC-AC) and leverage second-order cone relaxations, piecewise outer approximations, and optimization-based bounds tightening to guarantee a globally optimal solution at convergence. Numerical results on four benchmark problems illustrate the effectiveness of our algorithm, both in terms of convergence rate and solution quality.
24 POWER TRANSMISSION AND DISTRIBUTION↗
A Parallel Computing Framework for Finding the Supported Solutions to a Biobjective Network Optimization Problem
Abstract Solving multi‐objective combinatorial optimization problems can quickly become computationally challenging when applied to large networks generated from big data. Present‐day first‐rate Mixed Integer Programming (MIP) solvers have parallelism built‐in to take advantage of multicore architectures; but specialized network optimization algorithms that can often solve graph problems more efficiently than a general MIP solver are typically programmed serially. Thus, these network algorithm implementations do not take full advantage of modern multicore computer capabilities. Many parallel computing languages include a fork/join framework into their concurrency packages that allow for simple conversion of recursive serial algorithms to operate in parallel without having to use complicated low‐level message‐passing interfaces. Fork/join is particularly well suited to divide and conquer algorithms such as Non‐Inferior Set Estimation (NISE) method for computing the supported Pareto front of a multi‐objective optimization problem. This work develops a simple general parallel NISE (pNISE) implementation using the Java 7 concurrency tools, and then offers results from a specific implementation of solving a bi‐objective shortest path problem. The results indicate that this method is capable of sizeable speed‐ups on both small‐scale personal computers as well as large‐scale shared memory supercomputers. Finally, other network problems suitable to this method are discussed, including multi‐objective variants of the minimum spanning tree problem, transportation problem, assignment problem, maximum flow problem, and the minimum‐cost flow problem. Copyright © 2015 John Wiley & Sons, Ltd.
Medrano, Fernando Antonio↗
Parallel Solution of Optimal Gas Network Control Under Uncertainty.
Abstract not provided.
Bynum, Michael↗
Graphical solution of linear RLC networks
Rectangular diagrams for solving linear RLC networks by digital computer graphics
Ding, J. L.↗
Topological solution of bilateral switching networks
Bilateral switching networks synthesis by topological technique, tracing truth table optimum path by visual pattern detection
Mazer, L.↗
Intelligent network slicing and policy-based routing engine
One or more aspects of the present disclosure are directed to network optimization solutions provided as software agents (applications) executed on network nodes in a heterogenous multi-vendor environment to provide cross-layer network optimization and ensure availability of network resources to meet associated Quality of Experience (QoE) and Quality of Service (QoS). In one aspect, a network slicing engine is configured to receive at least one request from at least one network endpoint for access to the heterogeneous multi-vendor network for data transmission; receive information on state of operation of a plurality of communication links between the plurality of nodes; determine a set of data transmission routes for the request; assign a network slice for serving the request; determine, from the set of data transmission routes, an end-to-end route for the network slice; and send network traffic associated with the request using the network slice and over the end-to-end route.
Mody, Apurva N.↗