Source-sink Pairs Research Articles

Comment on: “Fluid flow and heat transfer characteristics of natural convection in square cavities due to discrete source-sink pairs” [International Journal of Heat and Mass Transfer 51 (2008) 5949–5957]

The following observations report incorrect/missing information, inaccurate mathematical expressions, and incorrect findings in the above-mentioned paper.

A three-stage evaluation model for biomass co-firing combined with carbon capture and storage (in oil wells) retrofit in coal-fired power plants based on multi-criteria decision-making: An example from Hebei Province, China

Coal-fired power plants can be retrofitted by biomass co-firing combined with CO2 capture and storage, reducing carbon emissions significantly. Site selection is an important task for the entire project, but little research has been done on this. Therefore, this paper proposed a three-level evaluation model. Firstly, alternative power plants and carbon sequestration sites (set oil wells as an example) were screened by feasibility evaluations. Secondly, source-sink pairs were performed based on the shortest distance between power plants and oil wells. Finally, source-sink pairs were evaluated with suitability evaluation. Entropy weight method (EWM) and Analytic hierarchy process (AHP) were used to calculate objective and subjective weights, respectively. Lagrangian optimization method was used to combine the two weights. The ranking results of alternative source-sink pairs were obtained through Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) improved by combined weight. An example of in-service power plants in Hebei Province was conducted. Engineering geology and reservoir characteristics were the most important considerations. D5 (source: Langfang thermal power plant, sink: Bieguzhuang - Jing 11 oil well) was the best choice of the five given candidates. The results of the study provided an evaluation framework for governments and investors in retrofitting power plants.

A holistic platform for accelerating sorbent-based carbon capture

Reducing carbon dioxide (CO2) emissions urgently requires the large-scale deployment of carbon-capture technologies. These technologies must separate CO2 from various sources and deliver it to different sinks1,2. The quest for optimal solutions for specific source–sink pairs is a complex, multi-objective challenge involving multiple stakeholders and depends on social, economic and regional contexts. Currently, research follows a sequential approach: chemists focus on materials design3 and engineers on optimizing processes4,5, which are then operated at a scale that impacts the economy and the environment. Assessing these impacts, such as the greenhouse gas emissions over the plant’s lifetime, is typically one of the final steps6. Here we introduce the PrISMa (Process-Informed design of tailor-made Sorbent Materials) platform, which integrates materials, process design, techno-economics and life-cycle assessment. We compare more than 60 case studies capturing CO2 from various sources in 5 global regions using different technologies. The platform simultaneously informs various stakeholders about the cost-effectiveness of technologies, process configurations and locations, reveals the molecular characteristics of the top-performing sorbents, and provides insights on environmental impacts, co-benefits and trade-offs. By uniting stakeholders at an early research stage, PrISMa accelerates carbon-capture technology development during this critical period as we aim for a net-zero world.

A network flow approach to a common generalization of Clar and Fries numbers

Clar number and Fries number are two thoroughly investigated parameters of plane graphs emerging from mathematical chemistry to measure stability of organic molecules. First, we introduce a common generalization of these two concepts for bipartite plane graphs, and then we extend it further to the notion of source-sink pairs of subsets of nodes in a general (not necessarily planar) directed graph. The main result is a min-max formula for the maximum weight of a source-sink pair. The proof is based on the recognition that the convex hull of source-sink pairs can be obtained as the projection of a network tension polyhedron. The construction makes it possible to apply any standard cheapest network flow algorithm to compute both a maximum weight source-sink pair and a minimizer of the dual optimization problem formulated in the min-max theorem. As a consequence, our approach gives rise to the first purely combinatorial, strongly polynomial algorithm to compute a largest (or even a maximum weight) Fries-set of a perfectly matchable plane bipartite graph and an optimal solution to the dual minimization problem.

An approximation algorithm for the -prize-collecting multicut problem in trees with submodular penalties

AbstractLet $T=(V,E)$ be a tree in which each edge is assigned a cost; let $\mathcal{P}$ be a set of source–sink pairs of vertices in V in which each source–sink pair produces a profit. Given a lower bound K for the profit, the K-prize-collecting multicut problem in trees with submodular penalties is to determine a partial multicut $M\subseteq E$ such that the total profit of the disconnected pairs after removing M from T is at least K, and the total cost of edges in M plus the penalty of the set of still-connected pairs is minimized, where the penalty is determined by a nondecreasing submodular function. Based on the primal-dual scheme, we present a combinatorial polynomial-time algorithm by carefully increasing the penalty. In the theoretical analysis, we prove that the approximation factor of the proposed algorithm is $(\frac{8}{3}+\frac{4}{3}\kappa+\varepsilon)$ , where $\kappa$ is the total curvature of the submodular function and $\varepsilon$ is any fixed positive number. Experiments reveal that the objective value of the solutions generated by the proposed algorithm is less than 130% compared with that of the optimal value in most cases.

Evaluation of Efficient CCUS System Design from Chemical Industry Emission in Indonesia

Carbon dioxide (CO2) emissions from industry significantly contribute to increasing CO2 in the atmosphere as the main cause of the Green House Gas (GHG) effect and climate change. CO2 emissions cause the need for evaluation in finding emission reduction systems. The CCUS (Carbon Capture Utilization and Storage) system is one of the most studied emission reduction systems. This study aims to obtain an intuitive and quantitative CCUS network design framework using GAMS (General Algebraic Modeling System) software with a mathematical approach. Several sources of CO2 emissions and potential absorbers are scattered in several regions in Indonesia. A mathematical approach was developed to optimize the amount of CO2 stored and utilized by varying the minimum time difference (dt min) between source and sink from 0, 3, 5, 8, to 10 years. The economic potential of the source-sink pair decreases with the change in dt with an average of 6.50 x 106 USD. Based on the potential economic value, the CCUS system with industrial CO2 emission sources has a positive value that can be applied in Indonesia.

Levelized-cost optimal design of long-distance CO2 transportation facilities

With the need to develop carbon-neutral technologies and reduce greenhouse gas emissions to avert climate change, carbon capture, storage and utilization (CCS/CCUS) techniques have emerged as effective pathways to achieve these targets. Despite being a critical aspect of CCS/CCUS chains, carbon dioxide transport is an astonishingly under-researched domain. This study presents an efficient and robust computational model to cost-optimally design of long distance carbon dioxide transport pipelines (trunk) connecting a source-sink pair. Several physical and topographical conditions have been accounted for to propose optimal design solutions for different case studies. This involves right-sizing of pipes and booster stations and placing the latter at the right locations. The implications of uncertainties in modelling of the costs have also been studied. The model is very flexible and general in the sense that it can work with a variety of cost models and design constraints. Further, unlike most studies, an appropriate hydrodynamic model for pressure and density calculations has been incorporated. Genetic algorithm and interior point methods have been employed to find optimal design parameters that minimize the “per ton levelized transportation cost”, and their performances have been compared. Results demonstrate that pipe diameters and elevation changes have the most significant impact on the pressure drop, optimal design parameters and the cost. Lastly, several improvements have been made over our previous study in this domain.

Recursive State Machine Guided Graph Folding for Context-Free Language Reachability

Context-free language reachability (CFL-reachability) is a fundamental framework for program analysis. A large variety of static analyses can be formulated as CFL-reachability problems, which determines whether specific source-sink pairs in an edge-labeled graph are connected by a reachable path, i.e., a path whose edge labels form a string accepted by the given CFL. Computing CFL-reachability is expensive. The fastest algorithm exhibits a slightly subcubic time complexity with respect to the input graph size. Improving the scalability of CFL-reachability is of practical interest, but reducing the time complexity is inherently difficult. In this paper, we focus on improving the scalability of CFL-reachability from a more practical perspective---reducing the input graph size. Our idea arises from the existence of trivial edges, i.e., edges that do not affect any reachable path in CFL-reachability. We observe that two nodes joined by trivial edges can be folded---by merging the two nodes with all the edges joining them removed---without affecting the CFL-reachability result. By studying the characteristic of the recursive state machines (RSMs), an alternative form of CFLs, we propose an approach to identify foldable node pairs without the need to verify the underlying reachable paths (which is equivalent to solving the CFL-reachability problem). In particular, given a CFL-reachability problem instance with an input graph G and an RSM, based on the correspondence between paths in G and state transitions in RSM, we propose a graph folding principle, which can determine whether two adjacent nodes are foldable by examining only their incoming and outgoing edges. On top of the graph folding principle, we propose an efficient graph folding algorithm GF. The time complexity of GF is linear with respect to the number of nodes in the input graph. Our evaluations on two clients (alias analysis and value-flow analysis) show that GF significantly accelerates RSM/CFL-reachability by reducing the input graph size. On average, for value-flow analysis, GF reduces 60.96% of nodes and 42.67% of edges of the input graphs, obtaining a speedup of 4.65× and a memory usage reduction of 57.35%. For alias analysis, GF reduces 38.93% of nodes and 35.61% of edges of the input graphs, obtaining a speedup of 3.21× and a memory usage reduction of 65.19%.

The B-Prize-Collecting Multicut Problem in Paths, Spider Graphs and Rings

Given a graph [Formula: see text], a set of [Formula: see text] source-sink pairs [Formula: see text] [Formula: see text] and a profit bound [Formula: see text], every edge [Formula: see text] has a cost [Formula: see text], and every source-sink pair [Formula: see text] has a profit [Formula: see text] and a penalty [Formula: see text]. The [Formula: see text]-prize-collecting multicut problem ([Formula: see text]-PCMP) is to find a multicut [Formula: see text] such that the objective cost, which consists of the total cost of the edges in [Formula: see text] and the total penalty of the pairs still connected after removing [Formula: see text], is minimized and the total profit of the disconnected pairs by removing [Formula: see text] is at least [Formula: see text]. In this paper, we firstly consider the [Formula: see text]-PCMP in paths, and prove that it is [Formula: see text]-hard even when [Formula: see text] for any [Formula: see text]. Then, we present a fully polynomial time approximation scheme (FPTAS) whose running time is [Formula: see text] for the [Formula: see text]-PCMP in paths. Based on this algorithm, we present an FPTAS whose running time is [Formula: see text] for the [Formula: see text]-PCMP in spider graphs, and an FPTAS whose running time is [Formula: see text] for the [Formula: see text]-PCMP in rings, respectively, where [Formula: see text] is the number of leaves of spider graph.

Unsteady buoyant convection of nanofluid in a porous annulus: impacts of size and location of thermal source–sink pairs

The current numerical investigation deals with natural convection in a nanofluid-saturated porous cylindrical annulus subjected to partial heating and cooling of side walls by adopting Brinkman-extended Darcy Model to govern the fluid flow in porous media. By choosing five different locations and four lengths of thermal source–sink pairs, the impact of discrete heating–cooling on fluid flow, thermal transport rates and thermal mixing in a porous annular enclosure has been addressed. From the vast range of numerical simulations, the results provide information on the proper size and location of source–sink combinations to dissipate maximum thermal transport along with better thermal mixing in the enclosure. The importance of porosity, nanoparticle concentration, Darcy and Rayleigh numbers on overall thermal dissipation rate has also been discussed. The results showed that identifying an optimum source–sink location along with an appropriate choice of other control parameters can lead to higher thermal transport enhancement and thermal mixing.

Non-Darcy nanoliquid buoyant flow and entropy generation analysis in an inclined porous annulus: Effect of source-sink arrangement

In several engineering and industrial applications, the primary challenge in the design of thermal devices is to minimize the entropy production with maximum energy dissipation so that the system efficiency could be enhanced. In particular, an inclined partially heated annulus is far challenging due to the presence of both tangential and normal gravity components, which produces major impacts on the fluid movement and associated transport rates as well as entropy production. From several important applications point of view, the current investigation is mainly focused to address the combined impacts of source-sink arrangements as well as the annular inclination on buoyant nanoliquid motion, thermal dissipation along with irreversibility distribution in a tilted porous annulus. The governing model equations are numerically solved by utilizing the finite difference based time-splitting and relaxation techniques. Using second-order finite difference approximation, the partial derivatives are approximated and the resulting system of algebraic equations are inverted using Thomas algorithm. The influence of various controlling parameters such as geometric inclination angle, nanoparticle shape, Darcy number, length and position of source-sink on fluid movement, thermal and entropy distribution are scrutinized in detail. Through a wide range of numerical experiments, it has been found that the annular inclination angle and location of source-sink arrangement plays a vital role on fluidity and flow patterns of nanoliquid in the porous saturated annulus. For smaller size of source-sink pair, higher thermal dissipation with minimal entropy production could be achieved, which is an important observation for the design of thermally efficient systems. We have also noticed that a better thermal transport rate with minimum irreversibility rate could be attained for a particular source-sink arrangement, in particular for γ=0∘, the staggered positioning of source-sink pair is beneficial rather than in-line arrangement. Among the various parameters arising in this analysis, the nanoparticle shape has been one of the key parameters to test the thermal efficiency. It has been predicted that the blade shaped nanoparticle induces better thermal efficiency, among the five different shapes of nanoparticle. The outcomes of this analysis could be utilized in applications, such as solar systems, electronic equipment cooling and heat exchangers.

0116 Slow oscillations promote long range effective communication: the key for memory consolidation in a broken down network

Abstract Introduction The relation between slow oscillations (SOs, <1Hz) during non-rapid eye movement (NREM) sleep and systems-level memory consolidation is one of the most robust findings in cognitive neuroscience. However, NREM is a brain state seemingly unfavorable to systems consolidation because a hallmark characteristic of this state is a breakdown in connectivity and reduction in synaptic plasticity with increasing depth of sleep. Our study addresses this apparent paradox and how SOs orchestrate neural communication. Methods We employed generalized partial directed coherence to estimate directional causal information flow between EEG channels across the electrode manifold during SO and non-SO periods. We examined the magnitude of causal information flow over the phase of SOs and found two peaks of flow preceding and following the trough of the SO. We categorized source-sink pairs of flows into three groups based on distance between source and sink of information flow. All the peak flows in each group were averaged and we tested relation between averaged magnitude of the flow and overnight episodic memory improvement using correlation test. Results The results reveal that NREM generally (non-SO periods) and during the SO trough show dampened neural communication. Causal communication during non-rapid eye movement sleep peaks during specific phases of the SO ( before and after SO trough), but only across long distances. Correlation test results showed that episodic memory improvement was predicted by peaks of information flow with longest distances between sinks and sources, and not by any other phase of the SO or non-SO period. Conclusion This work introduces a non-invasive approach to examine information processing during sleep, a behavioral stage whose function, until now, has been understood only at a delay. The findings represent a conceptual leap in understanding how slow oscillations unlock memory consolidation in a broken down network which is by promoting long range effective communication. This research will promote further investigations of understanding how brain oscillations alone and in nested rhythms promote network communication, as well as to investigate how these properties vary and predict patterns of deficits in clinical populations and aging humans. Support (If Any)

Numerical Investigations on Melting of Phase Change Material (PCM) with Different Arrangements of Heat Source-sink Pairs Under Microgravity

Numerical Investigations on Melting of Phase Change Material (PCM) with Different Arrangements of Heat Source-sink Pairs Under Microgravity

Transient thermogravitational convection for magneto hybrid nanofluid in a deep cavity with multiple isothermal source-sink pairs

An analysis of fluid flow and thermal transfer has been encountered numerically for natural convection of Ag–MgO (50%–50%) water hybrid nanoliquid in a vertical enclosure permeated by a uniform magnetic field and different sets of heat source-sink pairs. The control equations (Navier-Stokes equations) constituting streamfunction (ψ) – vorticity (ζ) formulations with energy equation are solved by adopting a higher order compact finite difference scheme. Furthermore, the consequence of emerging parameters affecting fluid flows and heat transfer, namely, Hartmann number (0 ≤ Ha ≤ 60), hybrid nanoparticles volume fraction (0 ≤ φhnp ≤ 0.02), Rayleigh number (103 ≤ Ra ≤ 106), different cases (Case-I-III), aspect ratios (AR = 0.5, 1, 2, 4) and internal heat generation or absorption (−2 ≤ Q ≤ 2) are analyzed generously. Experimentally established correlations for thermal conductivity and dynamic viscosity have been used throughout the study. Obtained results ascertain that the arrangement of heat sources and heat sinks put major impact on fluid flow and heat transfer. The presence of magnetic field causes a reduction in flow strength which leads to decrease in thermal transmission and the maximum value of stream function. Moreover, Ag–MgO hybrid nanoparticles play indispensable role to levitate the thermal transmission compared to other parameters.

Semi-decentralized energy routing algorithm for minimum-loss transmission in community energy internet

Modern power grid is becoming increasingly decentralized due to the rapid penetration of distributed energy sources. The concept of Energy Internet has been proposed as an open framework for interconnecting all distributed electrical devices via energy routers. However, efficient power transmission across the complex Energy Internet depends critically on the implementation of efficient energy routing algorithm. In this paper, an optimal energy routing algorithm is proposed to minimize transmission loss and achieve efficient energy routing. A semi-decentralized algorithm is proposed to distribute the computational load to individual energy routers for relieving the computational burden of the network control center. Routing information is shared among all energy routers via a common information sharing platform. With the proposed energy routing algorithm, transmission loss is further reduced and line congestion problem can be avoided by adopting multi-path transmissions. In the presence of multiple source-sink pairs and path overlapping, congestion and conflicts are resolved by cooperative routing. Transmission paths of the coalition formed are re-planned with the objective to minimize the total transmission loss of the coalition, and transmission loss savings are fairly assigned according to the Shapley values of members. Finally, the proposed energy routing algorithm is rigorously verified by numerical simulations.

Paths Through the Yeast Regulatory Network in Different Physiological States

We analyse paths through the regulatory networks that control gene-expression patterns in Yeast, in five different physiological states: cell cycle, DNA damage, stress response, diauxic shift, and sporulation. The network in each state is specified as a directed graph, containing different sets of edges connecting pairs selected from a combined set of 1475 nodes. Each network contains some nodes that have no parents, and others that have no children. We call these, respectively, ‘source’ and ‘sink’ nodes. For each network we enumerate paths between source and sink nodes.In a previous paper (Lesk and Konagurthu, 2020), we defined, extracted and compared the neighbourhoods of each transcription factor in different physiological states, and how the system reconfigures itself. Here we compare the usage of nodes and edges by different networks, and how they are assembled into paths. The picture that emerges is that the networks are not disjoint but show substantial sharing of nodes and edges; however, they assemble these materials into different sets of paths. Four of the networks, other than the cell-cycle network, contain paths between only a small fraction (<13%) of possible source-sink pairs. Although the cell-cycle network is not an outlier in terms of total number of nodes and edges, and number of sink nodes, it is very much an outlier in having a greater proportion of source-to-sink paths than the other networks.

Modeling of H2 Permeation through Electroless Pore-Plated Composite Pd Membranes Using Computational Fluid Dynamics.

This work focused on the computational fluid dynamics (CFD) modeling of H2/N2 separation in a membrane permeator module containing a supported dense Pd-based membrane that was prepared using electroless pore-plating (ELP-PP). An easy-to-implement model was developed based on a source–sink pair formulation of the species transport and continuity equations. The model also included the Darcy–Forcheimer formulation for modeling the porous stainless steel (PSS) membrane support and Sieverts’ law for computing the H2 permeation flow through the dense palladium film. Two different reactor configurations were studied, which involved varying the hydrogen flow permeation direction (in–out or out–in). A wide range of experimental data was simulated by considering the impact of the operating conditions on the H2 separation, such as the feed pressure and the H2 concentration in the inlet stream. Simulations of the membrane permeator device showed an excellent agreement between the predicted and experimental data (measured as permeate and retentate flows and H2 separation). Molar fraction profiles inside the permeator device for both configurations showed that concentration polarization near the membrane surface was not a limit for the hydrogen permeation but could be useful information for membrane reactor design, as it showed the optimal length of the reactor.

Specifying Callback Control Flow of Mobile Apps Using Finite Automata

Given the event-driven and framework-based architecture of Android apps, finding the ordering of callbacks executed by the framework remains a problem that affects every tool that requires inter-callback reasoning. Previous work has focused on the ordering of callbacks related to the Android components and GUI events. But the execution of callbacks can also come from direct calls of the framework (API calls). This paper defines a novel program representation, called Callback Control Flow Automata (CCFA) , that specifies the control flow of callbacks invoked via a variety of sources. We present an analysis to automatically construct CCFAs by combining two callback control flow representations developed from the previous research, namely, Window Transition Graphs (WTGs) and Predicate Callback Summaries (PCSs) . To demonstrate the usefulness of our representation, we integrated CCFAs into two client analyses: a taint analysis using FLOWDROID, and a value-flow analysis that computes source and sink pairs of a program. Our evaluation shows that we can compute CCFAs efficiently and that CCFAs improved the callback coverages over WTGs. As a result of using CCFAs, we obtained 33 more true positive security leaks than FLOWDROID over a total of 55 apps we have run. With a low false positive rate, we found that 22.76 percent of source-sink pairs we computed are located in different callbacks and that 31 out of 55 apps contain source-sink pairs spreading across components. Thus, callback control flow graphs and inter-callback analysis are indeed important. Although this paper mainly uses Android, we believe that CCFAs can be useful for modeling control flow of callbacks for other event-driven, framework-based systems.

Analysis of Critical Damage in the Communication Network. II. Guaranteed Functional Performance Estimates

In the computational experiments on a model of a multiuser communication and control network, changes in the system’s performance under destructive effects are studied. The vector of the maximal flows that can be transmitted independently between all nodes is used for the multicriteria assessment of the system’s functionality. The set of damage of various types is considered, consisting of specially selected vertices and minimal cuts; when they are removed, the maximal possible flow turns out to be zero for at least one source–sink pair. To assess the consequences and impact on the quality of communication of a specific destructive effect for each pair of nodes, the characteristic vector of the maximal permissible flows is formed. Computational experiments are carried out for all the damage from the given set and make it possible to determine a representative set of characteristic vectors. To obtain guaranteed estimates, a component-by-component analysis, sorting, and comparison by several criteria of all the performance indicators is performed. Final diagrams are constructed, reflecting the changes in the initial functional characteristics for the given set of targeted destructive actions. The aggregated assessments and indicators allow comparing the vulnerability and survivability of network systems with different structural features.

DecaDroid Classification and Characterization of Malicious Behaviour in Android Applications

Widespread use of Android-based applications on the smartphones has resulted in significant growth of security attack incidents. Malware-based attacks are the most common attacks on Android-based smartphones. To forestall malware from attacking the users, a much better understanding of Android malware and its behaviour is required. In this article, an approach to classify and characterise the malicious behaviour of Android applications using static features, data flow analysis, and machine learning techniques has been proposed. Static features like hardware components, permissions, Android components and inter-component communication along with unique source-sink pairs obtained from data flow analysis have been used to extract the features of the Android applications. Based on the features extracted, the malicious behaviour of the applications has been classified to their respective malware family. The proposed approach has given 95.19% accuracy rate and F1 measure of 92.19302 with the largest number of malware families classified as compared to previous work.