Flow Analysis Framework Research Articles

E-waste challenges of generative artificial intelligence.

Generative artificial intelligence (GAI) requires substantial computational resources for model training and inference, but the electronic-waste (e-waste) implications of GAI and its management strategies remain underexplored. Here we introduce a computational power-driven material flow analysis framework to quantify and explore ways of managing the e-waste generated by GAI, with a particular focus on large language models. Our findings indicate that this e-waste stream could increase, potentially reaching a total accumulation of 1.2-5.0 million tons during 2020-2030, under different future GAI development settings. This may be intensified in the context of geopolitical restrictions on semiconductor imports and the rapid server turnover for operational cost savings. Meanwhile, we show that the implementation of circular economy strategies along the GAI value chain could reduce e-waste generation by 16-86%. This underscores the importance of proactive e-waste management in the face of advancing GAI technologies.

Regional BDE-209 emission, environmental fate and risks: Methods establishment, data filling and feature analysis

BDE-209 is an emerging environmental contaminant that poses a significant threat to human health. Despite its inclusion in the Stockholm Convention, the current regional emission levels, environmental fate, and corresponding risks remain unclear, especially with the ongoing release of BDE-209 during the disposal of waste electrical and electronic equipment. The significant gaps in BDE-209 emission data highlight the need for a regional approach to better understand these issues. Therefore, we established a method to identify regional BDE-209 emissions, environmental fate, and risks in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) using a substance flow analysis framework, fugacity model, and risk model. Our results showed: (1) Despite the increasing pressure of electronic waste, emissions have decreased with gradual strengthening of restrictions. The stage with the highest contribution to emissions is flame-retardant plastic production, which accounts for 41 % of emissions, followed by informal treatment (36 %). (2) The largest BDE-209 emissions are into air and soil, at 7.23 t and 4.56 t, respectively, and the highest reserves are in soil and sediment. (3) Infants and young children have the highest levels of exposure and cancer risk. This research helps fill the multi-regional data gap for BDE-209 and clarify the complex regional emission situation in the GBA.

A Neural Network Approach to Physical Information Embedding for Optimal Power Flow

With the increasing share of renewable energy in the power system, traditional power flow calculation methods are facing challenges of complexity and efficiency. To address these issues, this paper proposes a new framework for AC optimal power flow analysis based on a physics-informed convolutional neural network (PICNN) approach, which enables the neural network to learn solutions that follow physical laws by embedding the power flow equations and other physical constraints into the loss function of the network. Compared with the traditional power flow calculation method, the calculation speed of this method is improved by 10–30 times. Compared to traditional neural network models, the method provides higher accuracy, with an average increase in accuracy of up to 2.5–10 times. In addition, this paper introduces a methodology to extract worst-case guarantees for violations of the neural network’s predicted power generation constraints, determining the worst possible violation that could result from any neural network output across the entire input domain, and taking appropriate measures to reduce the violation. The method is experimentally shown to be highly accurate and reliable for the AC optimal power flow (AC-OPF) analysis problem, while reducing the dependence on a large amount of labelled data.

A Conceptual Framework for Developing Intelligent Services (a Platform) for Transport Enterprises: The Designation of Key Drivers for Action

In the digital era, effective business management relies on dynamic risk analysis and real-time data integration, particularly amid the evolving landscape shaped by technological advancements and external factors such as climate change and global health crises. This study delves into the specific demands for digital services within the transportation sector, focusing on the crucial task of identifying an optimal data-driven management system (platform) to bolster transportation decision-making processes. The paper revolves around the formulation of a comprehensive conceptual framework for the development of intelligent services and platforms tailored explicitly to transport enterprises. Methodologically, a thorough analysis of critical infrastructure-related challenges was conducted, emphasizing the integration of a service-oriented approach to enhance overall functionality. Central to the paper’s approach is the careful navigation of conflicting user requirements, resource constraints, and the imperative of maintaining adaptability in service implementation. Additionally, a robust data flow analysis framework is presented, encompassing data collection, model building, and model extrapolation, which enables the generation of reliable outputs essential for informed decision-making. Notably, the study underscores the pivotal role played by the EN.I.R.I.S.S.T. research infrastructure in delivering essential services to the transportation domain, offering accessible data, user-friendly interfaces, and data analysis tools. The findings highlight the enthusiastic reception of the diverse services among potential users, indicating a strong willingness to engage and benefit from the proposed solutions. By emphasizing the integration of intelligent services, the paper seeks to present a systematic approach aimed at enhancing the efficiency, productivity, and competitive edge of transport enterprises through the strategic deployment of advanced technological solutions and proactive planning. This paper ultimately contributes cutting-edge research insights, empowering transportation managers, planners, and decision-makers with valuable resources for informed business intelligence and corporate strategy.

Noise-resilient quantum power flow

Quantum power flow (QPF) offers an inspiring direction for overcoming the computation challenge of power flow through quantum computing. However, the practical implementation of existing QPF algorithms in today's noisy-intermediate-scale quantum (NISQ) era remains limited because of their sensitivity to noise. This paper establishes an NISQ-QPF algorithm that enables power flow computation on noisy quantum devices. The main contributions include: (1) a variational quantum circuit (VQC)-based alternating current (AC) power flow formulation, which enables QPF using short-depth quantum circuits; (2) NISQ-compatible QPF solvers based on the variational quantum linear solver (VQLS) and modified fast decoupled power flow; and (3) an error-resilient QPF scheme to relieve the QPF iteration deviations caused by noise; (3) a practical NISQ-QPF framework for implementable and reliable power flow analysis on noisy quantum machines. Extensive simulation tests validate the accuracy and generality of NISQ-QPF for solving practical power flow on IBM's real, noisy quantum computers.

How changes in urban morphology translate into urban metabolisms of building stocks: A framework for spatiotemporal material flow analysis and a case study

Anthropogenic stocks are increasingly seen as potential reserves for secondary resources, which has led to a rapid development in research of urban metabolic systems. With regard to buildings and their associated material stocks and flows, one of the most critical shortcomings in the state-of-the-art is the knowledge gap for drivers, dynamics, patterns and linkages that affect the urban metabolism. This paper is premised on the idea that urban planning stirs up these material flows, so it should also adopt their sustainable management on its agenda. It presents an approach that highlights the intertwined nature of changing urban morphology and building material stocks and flows in space and time. An analytical framework, based on the principles of material flow analysis, is provided for an integrated, spatiotemporal study of urban morphology and urban metabolism of buildings, using building and plot data as the input and identifying internal processes of the urban metabolism as the output. The identified processes include greenfield development, infill construction, building replacement and shrinkage, each of which can be expected to have tangible yet very different material and environmental consequences in the form of embodied materials and CO2. The use of the framework is demonstrated with a case study in the Finnish city of Vantaa in 2000–2018. The case study shows patterns pertaining to a growing city unrestricted by geographic or historic factors, manifested as vast greenfield developments and replacement of a notably young building stock. As sustainability may soon call into question both these strategies, uncovering the material consequences of a city’s past urban (re)development strategies lay the foundation for using the presented approach proactively in planning support, in pursuit of more circular economy-based and low carbon cities.

Mapping the upstream journey of China's indium: A trade-linked substance flow analysis

As a metal raw material for developing emerging industries, many countries have increased the competition and storage of indium. As the country with the largest reserves and supply of indium resources, China's indium supply affects the development of global emerging industries. The current study of indium upstream of the chain is not comprehensive enough, ignoring some objects and the interaction between China and the rest of the world (RoW) in trade. This study establishes a trade-linked substance flow analysis (SFA) framework to explore the sources, pathways, and destinations of China's indium in the upstream flow of the industrial chain. The results indicate that from 2000 to 2019, in addition to the 21,335 tons mined domestically, 3603 tons of indium were brought to China through concentrates import. Faced with the input of so many resources, nearly 20,000 tons of indium flowed into the landfill, and 2526 tons of refined indium flowed into the stock because of the low recovery rate and insufficient downstream consumption. The accumulation of refined indium, disruption of indium refineries and manufacturers, and the dependence of foreign markets on China's low-priced refined indium have resulted in half of the refined indium produced being exported to developed countries. The production bottleneck of high-purity indium makes manufacturers import high-purity indium from these developed countries at high prices. The trade of indium metal causes the loss of resources and capital in China. This study implies that strengthening cooperation between indium refineries and manufacturers, breaking technical barriers, and increasing recovery rates can promote the sustainable development of indium resources in China and the RoW from the perspective of trade links.

Performance Analysis of Mobile Cloud Computing With Bursty Demand: A Tandem Queue Model

Resource-constrained end devices can offload computation to backend clouds. The stochastic wireless channel that an end device is connected to can introduce bursty computation demand to the cloud. Specifically, under good channel conditions, a device can transmit more data to the cloud, which consequently yields higher instantaneous computation demand. Conversely, poor channel conditions can result in lower instantaneous demand. The performance indicator for such a mobile cloud computing system is the average of the response time, which is the time span from the arrival of the computation demand at the backend cloud instance to the completion of its execution. The question we target in this paper is how resources should be provisioned for the backend cloud instance to address this bursty computation demand and guarantee a desired quality-of-service (QoS), namely, a user-specified average response time. To answer this question, we model the mobile cloud computing system as two tandem queues. We analyze this queueing network using the fluid flow analysis framework, and derive the analytical relationship between the required resource capacity at the backend cloud instance and the desired QoS, given the workload generation process at the end device and the wireless channel conditions. Having obtained the required resource capacity for a desired QoS, we then determine whether it is economical to provision this resource capacity by subscribing to the traditional static instance or the recently introduced burstable instance offered by public cloud providers. Finally, trace-driven simulations validate our theoretical results.

A data engineering framework for on-site end-of-life industrial operations

Sustainable initiatives for converting end-of-life (EoL) material flows into feedstocks would make a crucial contribution towards protecting our environment and mitigating the negative impacts of anthropogenic activities. Chemical flow analysis enables decision-makers to identify potential environmental releases and exposure pathways at the EoL stage and, therefore, improves the estimation of chemical exposure. Certain industrial facilities apply on-site pollution abatement operations, thereby constituting nodes of the chemical EoL management chain that can be evaluated and improved to enable greater circularity of materials. This work enhances and extends a recently published EoL data engineering framework by using publicly-available databases, data-driven models, and analytic hierarchy approaches to track chemicals, estimate releases, and potential exposure pathways at on-site industrial pollution management operations. The extended framework develops pollution abatement unit (PAU) technologies and estimates their efficiencies, chemical releases, exposure media, operating expenses, and capital expenditures. Relevant case studies based on the food and pharmaceutical industry sectors illustrate the application of the framework for chemical flow allocation and analysis of a chemical of concern and the benefits of integrating and extending the framework with data-driven and multi-criteria decision-making models. The results show how the enhanced framework designs and evaluates PAU technology systems for managing EoL chemical flows and provides release inventories and pathways for conducting chemical risk evaluation and exposure assessment of potential on-site EoL scenarios.

Awas: AADL information flow and error propagation analysis framework

Awas: AADL information flow and error propagation analysis framework

Tracing the global tin flow network: highly concentrated production and consumption

Tin is closely associated with daily life and scientific and technological development, being widely applied in electronic products (e.g., computers, mobile phones) and high-end manufacturing, but the sustainability of tin resources has aroused global concern. To understand the global tin trade and its implications, a material flow analysis framework is established in this study, to analyze the tin flow among countries during 1999–2018. Tin production is concentrated in nine countries, which account for more than 90% of global tin production; while tin consumption is concentrated in ten countries, which account for some 80% of total tin consumption. In addition, the level of economic development measured in GDP/capita, is found to be highly correlated with the role of a country in the global tin trade. The countries with low per capita GDP are usually principal tin producers and suppliers; while eight of the world's top ten refined tin consumers (accounting for about 70% of global consumption) are those with high per capita GDP. In addition, a significant correlation between refined tin consumption and GDP per capita is observed in developing countries, but this correlation weakens in developed countries. This study not only fills the data gap in global tin flow but also provides a reference and basis for tin resource decision making and for follow-up research on tin material flow.

A graph-based model framework for steady-state load flow problems of general multi-carrier energy systems

Coupling single-carrier networks into multi-carrier energy systems (MESs) has recently become more important. Conventional load flow models for the separate single-carrier networks are not able to capture the full extend of the coupling. Recently, different models for multi-carrier energy networks have been proposed, either using the energy hub (EH) concept, or using a case specific approach. Although the EH concept can be applied to a general MES, it is unclear how the EH should be represented in the graph of the MES. On the other hand, the case specific approaches are not easily applicable to general MESs. This paper presents a graph-based framework for steady-state load flow analysis of general MESs. Furthermore, the effect of coupling on the resulting integrated system of equations is investigated. The proposed framework is validated using a small MES. This example shows that our framework is applicable to a general MES, and that it generalizes both the EH concept and the case specific approach.

Physics‐based Pathline Clustering and Exploration

AbstractMost existing unsteady flow visualization techniques concentrate on the depiction of geometric patterns in flow, assuming the geometry information provides sufficient representation of the underlying physical characteristics, which is not always the case. To address this challenge, this work proposes to analyse the time‐dependent characteristics of the physical attributes measured along pathlines which can be represented as a series of time activity curves (TAC). We demonstrate that the temporal trends of these TACs can convey the relation between pathlines and certain well‐known flow features (e.g. vortices and shearing layers), which enables us to select pathlines that can effectively represent the physical characteristics of interest and their temporal behaviour in the unsteady flow. Inspired by this observation, a new TAC‐based unsteady flow visualization and analysis framework is proposed. The centre of this framework is a new similarity measure that compares the similarity of two TACs, from which a new spatio‐temporal, hierarchical clustering that classifies pathlines based on their physical attributes, and a TAC‐based pathline exploration and selection strategy are proposed. A visual analytic system incorporating the TAC‐based pathline clustering and exploration is developed, which also provides new visualizations to support the user exploration of unsteady flow using TACs. This visual analytic system is applied to a number of unsteady flow in 2D and 3D to demonstrate its utility. The new system successfully reveals the detailed structure of vortices, the relation between shear layer and vortex formation, and vortex breakdown, which are difficult to convey with conventional methods.

An urban material flow analysis framework and measurement method from the perspective of urban metabolism

Adapting a national-scale material flow analysis framework to an urban scale is difficult, so no researcher has yet developed a unified accounting and measurement framework at this scale. However, because cities represent major concentrations of resource consumption and pollution emission, this framework is urgently necessary. Based on the national-scale material flow analysis framework, we focused on the urban-scale material flow and divided a city into 8 compartments to develop a bottom-up accounting framework for urban material flow analysis using these compartments. The measurement and conversion methods for data that cannot be obtained directly from government statistical data were described. Two categories of material flow analysis indexes are explained, namely scale indexes and evaluation indexes. A case study of 13 cities in the Beijing-Tianjin-Hebei region of China demonstrated its application and the insights it provides. In the case cities, Tangshan, Tianjin, Handan showed the largest material consumption and fast rates of growth, and manufacturing is an important source of material consumption. The framework and methods developed in this study provide accounting templates that can be used for material flow analysis of cities at different stages of development both in China and elsewhere, thereby permitting a more unified and comparable accounting and analysis between studies.

Numerical Study of the Exchange Flow of the Persian Gulf Using an Extended Total Exchange Flow Analysis Framework

AbstractThe Total Exchange Flow analysis framework computes consistent bulk values quantifying the estuarine exchange flow using salinity coordinates since salinity is the main contributor to density in estuaries and the salinity budget is entirely controlled by the exchange flow. For deeper and larger estuaries temperature may contribute equally or even more to the density. That is why we included potential temperature as a second coordinate to the Total Exchange Flow analysis framework, which allows gaining insights in the potential temperature‐salinity structure of the exchange flow as well as to compute consistent bulk potential temperature and therefore heat exchange values with the ocean. We applied this theory to the exchange flow of the Persian Gulf, a shallow, semienclosed marginal sea, where dominant evaporation leads to the formation of hypersaline and dense Gulf water. This drives an inverse estuarine circulation which is analyzed with special interest on the seasonal cycle of the exchange flow. The exchange flow of the Persian Gulf is numerically simulated with the General Estuarine Transport Model from 1993 to 2016 and validated against observations. Results show that a clear seasonal cycle exists with stronger exchange flow rates in the first half of the year. Furthermore, the composition of the outflowing water is investigated using passive tracers, which mark different surface waters. The results show that in the first half of the year, most outflowing water comes from the southern coast, while in the second half most water originates from the northwestern region.

A mathematical framework for peristaltic flow analysis of non-Newtonian Sisko fluid in an undulating porous curved channel with heat and mass transfer effects

Background and objectivePeristaltic is one of the most frequently occurring phenomenon in biological systems. These systems of the human body (especially digestive, reproductive, respiratory, renal system) generally involve effects of curvature, porosity, rheology and heat transfer. Thus, in the present investigation we integrate heat transfer phenomenon with Sisko fluid flowing through porous medium bounded within curved wavy walls. The theoretical analysis presented under long wavelength approximation serves as a model for the creeping non-isothermal flow of blood through a diseased segment of the artery due to vasomotion (peristaltic motion) in the artery. MethodsThe highly nonlinear ordinary differential equation with appropriate boundary conditions is solved using a well-tested implicit finite difference scheme. A comparison of velocity profile for Newtonian, power-law and Sisko fluids is also presented. ResultsThe Sisko model predict higher values of velocity in the central core region than power-law and Newtonian model. The size of circulating bolus of fluid reduces with increasing permeability parameter. The symmetry in velocity and streamlines pattern is observed when dimensionless radius of curvature becomes very large.

Spatial-temporal analysis of carbon emissions embodied in interprovincial trade and optimization strategies: A case study of Hebei, China

Trade flows between provinces have led to the transfer of embodied carbon emissions. Therefore, when formulating carbon emission reduction policies for a province, it's necessary to consider the carbon emissions implied in trade. In this study, we established an interprovincial carbon flow analysis framework based on multi-regional input-output model, and we used China's 1997, 2002, 2007, and 2012 input-output data to make an empirical research of Hebei Province. The findings are as follows. Firstly, from 1997 to 2012, the embodied carbon emissions' net outflow of Hebei increased by 244.26 Mt, the number of the provinces that net inflowed carbon from Hebei increased from 18 to 22, and they extended from eastern coastal provinces and southern China to most parts of the country. Secondly, technological level and trade demand are the main factors affecting carbon emissions' net outflow, contributing −108.45 Mt and 352.71 Mt, respectively. On this basis, we developed a relationship model of the net outflow of carbon emission and commodity value to optimize the industrial development. Different from previous studies, our research has penetrated into every industry and every related province. We not only calculated the commodity transfer and embodied carbon transfer between Hebei Province and other provinces, and balanced the advantages and disadvantages of trade between key industries and provinces, then gave specific solutions and optimization measures, which has stronger practical meaning and guiding significance.

Setting the Common Ground: A Generic Framework for Material Flow Analysis of Complex Systems

Circular economy is currently characterized by various definitions, measurement approaches, and critical analyses thereof coexisting alongside each other. Whether the concept eventually prevails or collapses will depend to some extent on our success in harmonizing assessment methods among public, scientific, and private institutions, as well as across different materials and scales. Therefore, in this article, we present a generic material flow analysis framework that might serve as a common basis for circularity assessment, and test it by means of three case studies. It proved impossible to eliminate all subjective assumptions when transforming a real complex system into the generic framework, especially regarding the definition of by-products. However, by introducing subsystems it is at least possible to make such assumptions transparent. Therefore, adequate comparability across regions, materials, and scales is provided. Moreover, the generic system allows for coupled analysis of multiple materials simultaneously so that interactions between them can be studied, as well and a deeper insight into overall sustainability of the system can be gained.

Numerical issues of the Total Exchange Flow (TEF) analysis framework for quantifying estuarine circulation

Abstract. For more than a century, estuarine exchange flow has been quantified by means of the Knudsen relations which connect bulk quantities such as inflow and outflow volume fluxes and salinities. These relations are closely linked to estuarine mixing. The recently developed Total Exchange Flow (TEF) analysis framework, which uses salinity coordinates to calculate these bulk quantities, allows an exact formulation of the Knudsen relations in realistic cases. There are however numerical issues, since the original method does not converge to the TEF bulk values for an increasing number of salinity classes. In the present study, this problem is investigated and the method of dividing salinities, described by MacCready et al. (2018), is mathematically introduced. A challenging yet compact analytical scenario for a well-mixed estuarine exchange flow is investigated for both methods, showing the proper convergence of the dividing salinity method. Furthermore, the dividing salinity method is applied to model results of the Baltic Sea to demonstrate the analysis of realistic exchange flows and exchange flows with more than two layers.

Mixing Estimates for Estuaries

AbstractThe well-known Knudsen relations and the total exchange flow (TEF) analysis framework provide quantifications of exchange flow across an open boundary to the adjacent ocean in terms of bulk values (Knudsen theory: inflow and outflow volume or salinity) or with resolution in salinity space (TEF: profiles of volume and salt flux in salinity coordinates). In the present study, these theories are extended toward mixing of salinity, defined as the decay of salinity variance due to turbulent mixing. In addition to the advective fluxes, diffusive fluxes across the boundary are also considered now. These new Knudsen and TEF relations for mixing are derived by applying Gauss’s theorem to the salinity square and salinity variance equations. As a result of the analysis, four different Knudsen relations for the mixing in estuaries are derived. The first one is exact and considers nonperiodicity as well as nonconstancy of the inflow and outflow salinities. The other three formulations are approximate only, in the sense that either nonperiodicity or nonconstancy or both are relaxed. The simplest of those formulations has recently been derived by MacCready et al. and estimates the estuarine mixing as the product of inflow salinity, outflow salinity, and time-averaged river runoff. These four mixing estimates are systematically assessed by means of a number of idealized estuarine test cases. For periodic tidal flow, the simplest estimate still predicts the effective (physical plus numerical) mixing within an error of about 10%.