Low-grade waste heat recovery for wastewater treatment using clathrate hydrate based technology

Effectively recycling low-grade waste heat is crucial for advancing decarbonization and achieving net-zero emissions, yet current methodologies are limited by inefficiencies in extracting energy from sources with low exergy. This study introduces an innovative approach leveraging hydrate formation and dissociation to utilize low-grade waste heat in purifying wastewater. By directly heating (low-grade waste heat) liquid R134a, our method induces bubble formation, thereby enhancing hydrate nucleation and growth. Our system demonstrates exceptional energy efficiencies, reaching up to 23.5%, and exhibits a high removal efficiency for wastewater with high concentrations of organic and heavy metal contaminants, including methylene blue (86.4%), Cr3+ (98.0%), Ni2+ (98.3%), Zn2+ (98.0%), and Cu2+ (97.1%). This approach not only offers a sustainable pathway for waste heat utilization but also addresses critical challenges in wastewater treatment. This technology demonstrates substantial potential in both low-grade waste heat recovery and wastewater treatment

PENGARUH DEWAN KOMISARIS ASING, DEWAN KOMISARIS INDEPENDEN DAN KEPEMILIKAN SAHAM ASING TERHADAP NILAI PERUSAHAAN (STUDI EMPIRIS PADA PERUSAHAAN MANUFAKTUR YANG TERDAFTAR DI BEI TAHUN 2009-2011)

Penelitian ini bertujuan untuk menguji pengaruh dewan komisaris asing, dewan komisaris independen dan kepemilikan saham asing terhadap nilai perusahaan manufaktur yang terdaftar di BEI (Bursa Efek Indonesia) selama periode pengamatan (2009-2011).Penelitian ini merupakan penelitian empiris dengan pendekatan kuantitatif yang melibatkan penggunaan analisa statistik. Penelitian ini menggunakan data sekunder. Alat analisisnyang digunakan dalam penelitian ini adalah regresi linier berganda dengan bantuan sofware SPSS (Statistical Package for Social Scienc) Hasil penelitian menunjukkan bahwa dewan komisaris asing dan kepemilikan saham asing berpengaruh positif dan signifikan terhadap nilai perusahaan, sedangkan variabel dewan komisaris independen tidak mempunyai pengaruh yang signifikan terhadap nilai perusahaan

MLPerf Inference Benchmark

Machine-learning (ML) hardware and software system demand is burgeoning. Driven by ML applications, the number of different ML inference systems has exploded. Over 100 organizations are building ML inference chips, and the systems that incorporate existing models span at least three orders of magnitude in power consumption and five orders of magnitude in performance; they range from embedded devices to data-center solutions. Fueling the hardware are a dozen or more software frameworks and libraries. The myriad combinations of ML hardware and ML software make assessing ML-system performance in an architecture-neutral, representative, and reproducible manner challenging. There is a clear need for industry-wide standard ML benchmarking and evaluation criteria. MLPerf Inference answers that call. In this paper, we present our benchmarking method for evaluating ML inference systems. Driven by more than 30 organizations as well as more than 200 ML engineers and practitioners, MLPerf prescribes a set of rules and best practices to ensure comparability across systems with wildly differing architectures. The first call for submissions garnered more than 600 reproducible inference-performance measurements from 14 organizations, representing over 30 systems that showcase a wide range of capabilities. The submissions attest to the benchmark's flexibility and adaptability.Comment: ISCA 202

A Novel Multi-Objective Discrete Particle Swarm Optimization with Elitist Perturbation for Reconfiguration of Ship Power System

A novel multi-objective discrete particle swarm optimization with elitist perturbation strategy (EPSMODPSO) is proposed and applied to solve the reconfiguration problem of shipboard power system(SPS). The new algorithm uses the velocity to decide each particle to move one step toward positive or negative direction to update the position. An elitist perturbation strategy is proposed to improve the local search ability of the algorithm. Reconfiguration model of SPS is established with multiple objectives, and an inherent homogeneity index is adopted as the auxiliary estimating index. Test results of examples show that the proposed EPSMODPSO performs excellent in terms of diversity and convergence of the obtained Pareto optimal front. It is competent to solve network reconfiguration of shipboard power system and other multi-objective discrete optimization problems

Development of Ti-Bi-based nanomaterials to purify mercury in the simulated flue gas

The photocatalytic oxidation technology is a new technology for the oxidation treatment of Hg0 developed in the existing Wet Flue Gas Desulfurization (WFGD) equipment, in which the removal efficiency of Hg2+ is high and the removal efficiency of Hg0 is very low. When ultraviolet light (UV) is used to irradiate a substance containing TiO2 to pass the flue gas, photocatalytic catalytic oxidation reaction occurs, and Hg0 is oxidized to Hg2+, which is easily absorbed later in the WFGD apparatus, thereby improving the removal efficiency of mercury. The technology is still in the experimental development stage and needs further research. It has brought widespread interests to introduce surface defect or form interface heterostructure to improve the photocatalytic activity of the nanomaterials. The Ti-Bi-based nanomaterial photocatalyst with defect TiO2/BiOIO3 heterostructure has been fabricated via calcination method. The results showed that to introduce surface defect and form interface heterostructure on photocatalysts together can increase the response of the visible light, promoting the transfer velocity of the photocarriers and in turn suppressing the recombination of photo-generated electrons and holes, and this may become a developing trend in the near future

Development of Ti-Bi-based nanomaterials to purify mercury in the simulated flue gas

The photocatalytic oxidation technology is a new technology for the oxidation treatment of Hg0 developed in the existing Wet Flue Gas Desulfurization (WFGD) equipment, in which the removal efficiency of Hg2+ is high and the removal efficiency of Hg0 is very low. When ultraviolet light (UV) is used to irradiate a substance containing TiO2 to pass the flue gas, photocatalytic catalytic oxidation reaction occurs, and Hg0 is oxidized to Hg2+, which is easily absorbed later in the WFGD apparatus, thereby improving the removal efficiency of mercury. The technology is still in the experimental development stage and needs further research. It has brought widespread interests to introduce surface defect or form interface heterostructure to improve the photocatalytic activity of the nanomaterials. The Ti-Bi-based nanomaterial photocatalyst with defect TiO2/BiOIO3 heterostructure has been fabricated via calcination method. The results showed that to introduce surface defect and form interface heterostructure on photocatalysts together can increase the response of the visible light, promoting the transfer velocity of the photocarriers and in turn suppressing the recombination of photo-generated electrons and holes, and this may become a developing trend in the near future

Hybrid Triboelectric Nanogenerators: From Energy Complementation to Integration

Energy collection ways using solar energy, wave, wind, or mechanical energy have attracted widespread attention for small self-powered electronic devices with low power consumption, such as sensors, wearable devices, electronic skin, and implantable devices. Among them, triboelectric nanogenerator (TENG) operated by coupling effect of triboelectrification and electrostatic induction has gradually gained prominence due to its advantages such as low cost, lightweight, high degree of freedom in material selection, large power, and high applicability. The device with a single energy exchange mechanism is limited by its conversion efficiency and work environment and cannot achieve the maximum conversion of energy. Thus, this article reviews the research status of different types of hybrid generators based on TENG in recent years. Hybrid energy generators will improve the output performance though the integration of different energy exchange methods, which have an excellent application prospect. From the perspective of energy complementation, it can be divided into harvesting mechanical energy by various principles, combining with harvesters of other clean energy, and converting mechanical energy or various energy sources into hydrogen energy. For integrating multitype energy harvesters, mechanism of single device and structural design of integrated units for different application scenarios are summarized. The expanding energy harvesting efficiency of the hybrid TENG makes the scheme of self-charging unit to power intelligent mobile electronic feasible and has practical significance for the development of self-powered sensor network

An Integrated Decision-Making Model for Transformer Condition Assessment Using Game Theory and Modified Evidence Combination Extended by D Numbers

The power transformer is one of the most critical and expensive components for the stable operation of the power system. Hence, how to obtain the health condition of transformer is of great importance for power utilities. Multi-attribute decision-making (MADM), due to its ability of solving multi-source information problems, has become a quite effective tool to evaluate the health condition of transformers. Currently, the analytic hierarchy process (AHP) and Dempster–Shafer theory are two popular methods to solve MADM problems; however, these techniques rarely consider one-sidedness of the single weighting method and the exclusiveness hypothesis of the Dempster–Shafer theory. To overcome these limitations, this paper introduces a novel decision-making model, which integrates the merits of fuzzy set theory, game theory and modified evidence combination extended by D numbers, to evaluate the health condition of transformers. A four-level framework, which includes three factors and seventeen sub-factors, is put forward to facilitate the evaluation model. The model points out the following: First, the fuzzy set theory is employed to obtain the original basic probability assignments for all indices. Second, the subjective and objective weights of indices, which are calculated by fuzzy AHP and entropy weight, respectively, are integrated to generate the comprehensive weights based on game theory. Finally, based on the above two steps, the modified evidence combination extended by D numbers, which avoids the limitation of the exclusiveness hypothesis in the application of Dempster–Shafer theory, is proposed to obtain the final assessment results of transformers. Case studies are given to demonstrate the proposed modeling process. The results show the effectiveness and engineering practicability of the model in transformer condition assessment

A Study on the Suitable Areas for Growing Apricot Kernels in China Based on the MaxEnt Model

Research on the climatic adaptation of the apricot kernels (Prunus armeniaca L.) has significant meaning for optimizing their cultivation and utilizing climatic resources effectively. This research utilizes geographical distribution data, climatic environmental factors, soil data, and altitude data of the apricot kernel in China. By employing the maximum entropy model (MaxEnt) and geographic information system (ArcGIS), we identify the key factors influencing the distribution of apricot kernels in China and suitable areas for their cultivation. Our findings reveal that annual precipitation, frequency of frost days in April, altitude, soil pH, and effective soil water content are the primary environmental factors impacting the distribution of apricot kernels in China. We classify the planting suitability zones into four categories. The areas characterized by annual precipitation ranging from 330.54 mm to 616.42 mm, frost day frequency of 2.68 to 19.15 days in April, altitude between 84.22 m and 831.81 m, pH values ranging from 7.5 to 8.6, and effective soil water content of 1.16 to 3.88 are deemed most suitable for growing apricot kernels. The most suitable areas correspond to the main growing areas in reality. Given the limited existing research on suitable areas for apricot kernel cultivation, this study provides a scientific foundation for promoting the cultivation of apricot kernels