Search Results (40)

Heat integration has been widely and successfully practiced for recovering thermal energy in process plants for decades. It is usually implemented through synthesizing heat exchanger networks (HENs). It is recognized that mechanical energy, another form of energy that involves pressure-driven transport of compressible fluids, can be recovered through synthesizing work exchanger networks (WENs). One type of WEN employs piston-type work exchangers, which demonstrates techno-economic attractiveness. A thermodynamic-model-based energy recovery targeting method was developed to predict the maximum amount of mechanical energy feasibly recoverable by piston-type work exchangers prior to WEN configuration generation. In this work, a heat-integrated WEN synthesis methodology embedded by the thermodynamic model is introduced, by which the maximum mechanical energy, together with thermal energy, can be cost-effectively recovered. The methodology is systematic and general, and its efficacy is demonstrated through two case studies that highlight how the proposed methodology leads to designs simpler than those reported by other researchers while also having a lower total annualized cost (TAC). Full article

As a non-renewable resource, oil faces increasing demand, and the remaining oil recovery rates in existing oil fields still require improvement. The primary objective of this study is to investigate the impact of pore structure parameters on the distribution and recovery of residual oil after polymer flooding by constructing a digital pore network model. Using this model, the study visualizes the post-flooding state of the model with 3DMAX-9.0 software and employs a range of simulation methods, including a detailed analysis of the pore size, coordination number, pore–throat ratio, and wettability, to quantitatively assess how these parameters affect the residual oil distribution and recovery. The research shows that the change in the distribution of pore sizes leads to a decrease in cluster-shaped residual oil and an increase in columnar residual oil. An increase in the coordination number increases the core permeability and reduces the residual oil; for example, when the coordination number increases from 4.3 to 6, the polymer flooding recovery rate increases from 24.57% to 30.44%. An increase in the pore–throat ratio reduces the permeability and causes more residual oil to remain in the throat; for example, when the pore–throat ratio increases from 3.2 to 6.3, the total recovery rate decreases from 74.34% to 63.72%. When the wettability changes from oil-wet to water-wet, the type of residual oil gradually changes from the difficult-to-drive-out columnar and film-shaped to the more easily recoverable cluster-shaped; for example, when the proportion of water-wet throats increases from 0.1:0.9 to 0.6:0.4, the water flooding recovery rate increases from 35.63% to 51.35%. Both qualitative and quantitative results suggest that the digital pore network model developed in this study effectively predicts the residual oil distribution under different pore structures and provides a crucial basis for optimizing residual oil recovery strategies. Full article

The widespread use of Unmanned Underwater Vehicles (UUVs) in seafloor observatory networks highlights the need for docking stations to facilitate rapid recharging and effective data transfer. Floating docks are promising due to their flexibility, ease of deployment, and recoverability. To enhance understanding and optimize UUV docking with floating docks, we employ dynamic fluid body interaction (DFBI) to construct a seabed moored suspended dock (SMSD) model that features a guiding funnel, a suspended body, and a catenary of a mooring chain. This model simulates SMSD equilibrium stabilization in various ocean currents. Then, a UUV docking model with contact coupling is developed from the SMSD model to simulate the dynamic contact response during docking. The accuracy of the docking model was validated using previous experimental data. Through investigation of the UUV docking response results, sensitivity studies relating to volume, moment of inertia, mass, and catenary stiffness were conducted, thereby guiding SMSD optimization. Finally, sea tests demonstrated that the SMSD maintained stability before docking. During docking, the SMSD’s rotation facilitated smooth UUV entry. After the UUV docked, the SMSD was restored to its original azimuth, confirming its adaptability, stability, and reliability. Full article

In order to improve the effect of injection–production coupling development to improve crude oil recovery in complex fault-block reservoirs, we carried out a physical simulation experiment based on a sandpack model of transforming water-driven development into injection–production coupling development and quantitatively evaluated the influence of rounds of injection pressure coupling on the crude oil mobilization in reservoirs with different permeability levels and on oil recovery. Meanwhile, the characteristics of residual oil were studied via a numerical simulation method. The mechanism of increased oil production via injection–production coupling development was revealed by analyzing the water and oil contents, formation pressure, and streamline fields through the establishment of mechanism models. The results of the physical experiment show that injection–production coupling can improve the recovery effect of medium- and low-permeability reservoirs by 55.66%. With an increase in the injection pressure, the oil recovery percentage of the low-permeability sandpack model at 20 MPa is 100%, and this study finds that injection–production coupling is the main way to develop the recoverable oil in a low-permeability reservoir. The numerical simulation results show that among the four remaining oil distribution types (interwell-enriched, low-permeability zone-enriched, well network imperfection, and mismatch between injection and production), the interwell-enriched type of the remaining oil reserves accounts for the highest proportion (48.52%). The simulation results of the mechanism model show that water-driven development easily leads to streamline solidification, resulting in ineffective circulation of the injected water. Compared with conventional water-driven development, the pressure propagation range is significantly increased in injection–production coupling development. The reservoir streamline distribution is more continuous and uniform, and the flooding wave is wider in volume and range. This research provides a theoretical basis for the injection–production coupling technology policy in complex fault-block reservoirs. Full article

Load-bearing biological tissues, such as cartilage and muscles, exhibit several crucial properties, including high elasticity, strength, and recoverability. These characteristics enable these tissues to endure significant mechanical stresses and swiftly recover after deformation, contributing to their exceptional durability and functionality. In contrast, while hydrogels are highly biocompatible and hold promise as synthetic biomaterials, their inherent network structure often limits their ability to simultaneously possess a diverse range of superior mechanical properties. As a result, the applications of hydrogels are significantly constrained. This article delves into the design mechanisms and mechanical properties of various tough hydrogels and investigates their applications in tissue engineering, flexible electronics, and other fields. The objective is to provide insights into the fabrication and application of hydrogels with combined high strength, stretchability, toughness, and fast recovery as well as their future development directions and challenges. Full article

In this paper, a fault recovery strategy for a distribution network based on a pigeon-inspired optimization (PIO) algorithm is proposed to improve the recoverability of the network considering the increased proportion of distributed energy resources. First, an improved Kruskal algorithm-based island partitioning scheme is proposed considering the electrical distance and important load level during the island partitioning process. Secondly, a mathematical model of fault recovery is established with the objectives of reducing active power losses and minimizing the number of switching actions. The conventional PIO algorithm is improved using chaos, reverse strategy, and Cauchy perturbation strategy, and the improved pigeon-inspired optimization (IPIO) algorithm is applied to solve the problem of fault recovery of the distribution network. Finally, simulation analysis is carried out to verify the effectiveness of the proposed PIO algorithm considering a network restauration problem after fault. The results show that compared with traditional algorithms, the proposed PIO algorithm has stronger global search capability, effectively improving the node voltage after restauration and reducing circuit loss. Full article

For this study, we investigated efficient strategies for the recovery of individual links in power grids governed by the direct current (DC) power flow model, under random link failures. Our primary objective was to explore the efficacy of recovering failed links based solely on topological network metrics. In total, we considered 13 recovery strategies, which encompassed 2 strategies based on link centrality values (link betweenness and link flow betweenness), 8 strategies based on the products of node centrality values at link endpoints (degree, eigenvector, weighted eigenvector, closeness, electrical closeness, weighted electrical closeness, zeta vector, and weighted zeta vector), and 2 heuristic strategies (greedy recovery and two-step greedy recovery), in addition to the random recovery strategy. To evaluate the performance of these proposed strategies, we conducted simulations on three distinct power systems: the IEEE 30, IEEE 39, and IEEE 118 systems. Our findings revealed several key insights: Firstly, there were notable variations in the performance of the recovery strategies based on topological network metrics across different power systems. Secondly, all such strategies exhibited inferior performance when compared to the heuristic recovery strategies. Thirdly, the two-step greedy recovery strategy consistently outperformed the others, with the greedy recovery strategy ranking second. Based on our results, we conclude that relying solely on a single metric for the development of a recovery strategy is insufficient when restoring power grids following link failures. By comparison, recovery strategies employing greedy algorithms prove to be more effective choices. Full article

To recover thermal energy from different sources, its quality and possibilities for utilisation are essential. The wide range of engineering solutions includes a direct connection to the district heating (DH) system and the integration of low-quality heat using heat pumps to increase the temperature level of recoverable heat. Therefore, this article compares waste heat valorisation strategies for integration into existing DH networks, low-temperature DH, and ultra-low heat supply systems using the multi-criteria assessment method. In addition, a local scale assessment was performed to identify the waste heat role in existing RES-based DH systems. The results show that the highest waste heat valorisation rate could be reached when integrated into low-temperature DH systems due to high waste heat potential and suitable temperature conditions. However, a local scale assessment shows a significant impact on the already implemented solar technologies, as waste heat could cover around 70% of the summer heat load. Full article

Many “Industry 4.0” applications rely on data-driven methodologies such as Machine Learning and Deep Learning to enable automatic tasks and implement smart factories. Among these applications, the automatic quality control of manufacturing materials is of utmost importance to achieve precision and standardization in production. In this regard, most of the related literature focused on combining Deep Learning with Nondestructive Testing techniques, such as Infrared Thermography, requiring dedicated settings to detect and classify defects in composite materials. Instead, the research described in this paper aims at understanding whether deep neural networks and transfer learning can be applied to plain images to classify surface defects in carbon look components made with Carbon Fiber Reinforced Polymers used in the automotive sector. To this end, we collected a database of images from a real case study, with 400 images to test binary classification (defect vs. no defect) and 1500 for the multiclass classification (components with no defect vs. recoverable vs. non-recoverable). We developed and tested ten deep neural networks as classifiers, comparing ten different pre-trained CNNs as feature extractors. Specifically, we evaluated VGG16, VGG19, ResNet50 version 2, ResNet101 version 2, ResNet152 version 2, Inception version 3, MobileNet version 2, NASNetMobile, DenseNet121, and Xception, all pre-trainined with ImageNet, combined with fully connected layers to act as classifiers. The best classifier, i.e., the network based on DenseNet121, achieved a 97% accuracy in classifying components with no defects, recoverable components, and non-recoverable components, demonstrating the viability of the proposed methodology to classify surface defects from images taken with a smartphone in varying conditions, without the need for dedicated settings. The collected images and the source code of the experiments are available in two public, open-access repositories, making the presented research fully reproducible. Full article

This research aims to identify, categorize, and prioritize the barriers hindering the implementation of the circular economy (CE) within food supply chains. To do so, a hybrid multi-criteria decision analysis method, combining a decision-making trial and evaluation laboratory (DEMATEL) and the analytical network process (ANP), is used to analyze multiple determinants extracted from the target literature and the expert panel opinions. As a result, the key barriers to implementing the CE in the food sector were identified and ranked through the hybrid multi-criteria decision analysis. The practicality and validity of the model in the case of causal relationships that have hindered the CE transition in the food sector in Iran, as a developing country, are examined. A total of 15 barriers in six dimensions were analyzed. The “technical and technological capabilities”, “financial issues”, and “production issues” were distinguished as the most important dimensions. Moreover, “lack of circular design and innovative packaging to reduce food waste”, “high cost of CE implementation”, and “insufficient use of reusable, recyclable, and recoverable materials” were identified as the key barriers in the CE transition in food supply chains. The findings of this study revealed that “government policies”, “culture”, and “financial issues” were the most significant “cause” dimensions, which could leverage the elimination of “effect” dimensions, including “technical and technological capabilities”, “management and collaboration issues”, and “production issues”. The identified challenges and barriers pave the way for CE implementation and outline focal points for decision makers to mobilize their efforts in this regard. The findings can effectively contribute to the domain by providing insightful guidelines for the government and associated authorities, policymakers, and all stakeholders within the food supply chain to support the CE transition in the food sector. Full article

Information and communication technology (ICT)-based products have a significant effect on increasing levels of waste electrical and electronic equipment (WEEE) or electronic waste (e-waste) due to their shorter lifespan as a result of rapid technological changes. Mobile phones are the most popular ICT products, and their market share is increasing gradually. Therefore, effective management of waste mobile phones (WMP) is sought as their recovery brings enormous economic and regulatory benefits. Forecasting the quantities of WMP and their recoverable material content generates valuable data for the related stakeholders in the circular economy (CE) in the design and management of their supply chain networks. This paper presents an approach to determining the WMP quantity for Turkey considering the system from sales to end-of-life (EOL) stages and the years between 2001 and 2035. The proposed model includes two main parts: estimation and forecasting. Firstly, the generated WMP quantity is estimated based on dynamic lifespan and sales using the Distribution Delay (DD) Method considering the years from 2001 to 2020. To select the most suitable model for future projection, seven different time series methods (e.g., Simple Exponential Smoothing, Holt’s, Logistics, Gompertz, Logarithmic, Bass, and ARIMA models) are considered to estimate the generated WMP. For the given data, the Holt’s Method is determined to be the best method to forecast the WMP quantities for the years from 2021 to 2035. In addition, waste materials amount and revenue potentials are estimated for the years from 2001 to 2035. The WMP for Turkey is expected to be approximately 11.5 million units and has a 52 million US$ revenue potential in 2035. The present study contributes to the literature, as it is the first holistic forecasting study on the quantification of WMPs in Turkey. Moreover, since WMPs include remarkable recovery potential in terms of CE, the data and findings of this study may help policymakers, governments, producers, consumers, and all stakeholders to establish effective e-waste management approaches. Full article

This research proposes a methodology with multi-objective optimization for the placement of Pumps operating As Turbines (PATs), energizing street lighting, devices for monitoring the water network, and charging stations for small electric vehicles such as bikes and scooters. This methodology helps to find the most profitable project for benefiting life quality and energy recovery through pumps operating as turbines, replacing virtual pressure reduction valves to locate the best point for decreasing pressure. PATs are selected by maximizing power recovery and minimizing pressure in the system as well as maximizing recoverable energy. Benefits analyzed include the reduction of carbon dioxide emissions and fuel use, as well as the saving of electricity consumption and benefiting socio-economic impact with street lighting, monitoring, and charging station. It was considered that each PAT proposed by the methodology will supply a street light pole, a station for monitoring the water network, and a charging station; under these established conditions, the return on investment is up to 1.07 at 12 years, with a power generation of 60 kWh per day. Full article

Currently, hydrogels simultaneously featuring high strength, high toughness, superior recoverability, and benign anti-fatigue properties have demonstrated great application potential in broad fields; thus, great efforts have been made by researchers to develop satisfactory hydrogels. Inspired by the double network (DN)-like theory, we previously reported a novel high-strength/high-toughness hydrogel which had two consecutive energy-dissipation systems, namely, the unzipping of coordinate bonds and the dissociation of the crystalline network. However, this structural design greatly damaged its stretchability, toughness recoverability, shape recoverability, and anti-fatigue capability. Thus, we realized that a soft/ductile matrix is indispensable for an advanced strong tough hydrogel. On basis of our previous work, we herein reported a modified energy-dissipation model, namely, a “binary DN-like structure” for strong tough hydrogel design for the first time. This structural model comprises three interpenetrated polymer networks: a covalent/ionic dually crosslinked tightened polymer network (stiff, first order network), a constrictive crystalline polymer network (sub-stiff, second order network), and a ductile/flexible polymer network (soft, third order network). We hypothesized that under low tension, the first order network served as the sacrificing phase through decoordination of ionic crosslinks, while the second order and third order networks together functioned as the elastic matrix phase; under high tension, the second order network worked as the energy dissipation phase (ionic crosslinks have been destroyed at the time), while the third order network played the role of the elastic matrix phase. Owing to the “binary DN-like” structure, the as-prepared hydrogel, in principle, should demonstrate enhanced energy dissipation capability, toughness/shape recoverability, and anti-fatigue/anti-tearing capability. Finally, through a series of characterizations, the unique “binary DN-like” structure was proved to fit well with our initial theoretical assumption. Moreover, compared to other energy-dissipation models, this structural design showed a significant advantage regarding comprehensive properties. Therefore, we think this design philosophy would inspire the development of advanced strong tough hydrogel in the future. Full article

Flexible self-healing composite was fabricated based on blending the bromobutyl rubber (BIIR) and epoxide natural rubber (ENR) filled with hybrid fillers of carbon nanotubes (CNT) and carbon black (CB). To achieve self-recoverability, modification of BIIR was carried out through butyl imidazole (IM), and the healing capability was then activated by the addition of bis(triethoxysilylpropyl)tetrasulfide (TESPT), which resulted in good dispersion of CNT/CB in BIIR/ENR blends. The silanization of TESPT and CNT/CB hybrid filler surfaces was confirmed by attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy. Adding CNT/CB and incorporating TESPT into the composites effectively improved the curing and mechanical properties of the blends in terms of estimated crosslink density and tensile modulus. Further, the self-healing propagation rate was enhanced by the thermal conductivity of fillers and the ion–dipole intermolecular forces between the rubber chains, leading to the highest abrasion resistance and electrical conductivity. Using an environmentally friendly process, the recyclability of the self-healing composites was improved by the re-compression of the samples. With this, the constant conductivity relating to the rearrangement of the CNT/CB network is examined related to the usability of the composites at 0 and 60 °C. The conductive composites filled with a TESPT silane coupling agent present an opportunity for vehicle tires and other self-repairing applications. Full article

The use of Electronic Health Record (EHR) systems has emerged with the continuous advancement of the Internet of Things (IoT) and smart devices. This is driven by the various advantages for both patients and healthcare providers, including timely and distant alerts, continuous control, and reduced cost, to name a few. However, while providing these advantages, various challenges involving heterogeneity, scalability, and network complexity are still open. Patient security, data privacy, and trust are also among the main challenges that need more research effort. To this end, this paper presents an implementation of a biometric-based blockchain EHR system (BBEHR), a prototype that uniquely identifies patients, enables them to control access to their EHRs, and ensures recoverable access to their EHRs. This approach overcomes the dependency on the private/public key approach used by most blockchain technologies to identify patients, which becomes more crucial in situations where a loss of the private key permanently hinders the ability to access patients’ EHRs. Our solution covers component selection, high-level implementation, and integration of subsystems, was well as the coding of a prototype to validate the mitigation of the risk of permanent loss of access to EHRs by using patients’ fingerprints. A performance analysis of BBEHR showed our system’s robustness and effectiveness in identifying patients and ensuring access control for their EHRs by using blockchain smart contracts with no additional overhead. Full article