Energy Consumption Ratio Research Articles

Information-Centric IoT-Based Smart Farming with Dynamic Data燨ptimization

Smart farming has become a strategic approach of sustainable agriculture management and monitoring with the infrastructure to exploit modern technologies, including big data, the cloud, and the Internet of Things (IoT). Many researchers try to integrate IoT-based smart farming on cloud platforms effectively. They define various frameworks on smart farming and monitoring system and still lacks to define effective data management schemes. Since IoT-cloud systems involve massive structured and unstructured data, data optimization comes into the picture. Hence, this research designs an Information-Centric IoT-based Smart Farming with Dynamic Data Optimization (ICISF-DDO), which enhances the performance of the smart farming infrastructure with minimal energy consumption and improved lifetime. Here, a conceptual framework of the proposed scheme and statistical design model has been well defined. The information storage and management with DDO has been expanded individually to show the effective use of membership parameters in data optimization. The simulation outcomes state that the proposed ICISF-DDO can surpass existing smart farming systems with a data optimization ratio of 97.71%, reliability ratio of 98.63%, a coverage ratio of 99.67%, least sensor error rate of 8.96%, and efficient energy consumption ratio of 4.84%.

Task Offloading in Multi-Access Edge Computing Enabled UAV-Aided Emergency Response Operations

In emergency response operations, using uncrewed aerial vehicles (UAVs) has recently become a promising solution due to their flexibility and easy deployment. However, tasks performed by the UAVs, e.g., object detection and human pose recognition, usually require a high computation capacity and energy supply. Furthermore, offloading tasks to the edge server-equipped base stations may not always be possible because of a lack of infrastructure or distance. Therefore, UAV-aided edge servers can be deployed near UAV scouts to provide computing services. However, a UAV can not perform all types of tasks since it has limitations on memory, available software, central processing unit (CPU), and graphics processing unit (GPU) capacity. Therefore, this study focuses on task offloading (TO), power, and computation resource allocation (PRA) problems in a multi-layer MEC-enabled UAV network while taking into account CPU and GPU requirements of tasks, the capacity of the devices (i.e., computational resources, power, and energy), and limitations on the type of tasks a UAVs can perform. The problem is formulated as a non-convex mixed-integer nonlinear problem to minimize the weighted sum of the maximum energy consumption ratio in the network and total task execution latency ratio, and then decomposed and converted into an integer and a convex problem. A messy genetic algorithm (mGA)-based TO and PRA strategy (mGA-TPR) is proposed to solve the problem, where two PRA strategies are based on the Karush–Kuhn–Tucker conditions used to solve the PRA problem. Simulation results verify that the proposed scheme can outperform the baseline methods.

Pulsatile energy consumption as a surrogate marker for vascular afterload improves with time post transcatheter aortic valve replacement in patients with aortic stenosis.

The effect of arterial stiffening on elevated pulsatile left ventricular afterload patients with aortic stenosis (AS) is pronounced beyond systemic hypertension. Circulatory afterload pulsatile efficiency (CAPE) is a marker of vascular function, defined as the ratio of steady state energy consumption (SEC) to maintain systemic circulation and pulsatile energy consumption (PEC). Twenty patients aged 80 ± 7 years were assessed at baseline and a median of 60 days post transcatheter aortic valve replacement (TAVR), with pulsatile vascular load calculated using simultaneous radial applanation tonometry derived aortic pressure and cardiac magnetic resonance phase-contrast imaging derived ascending aortic flow. Eight out of 20 patients had a reduction in PEC post TAVR, and the reduction of PEC correlated strongly with the number of days post TAVR (R = 0.62, P < 0.01). Patients assessed within the 100 days of TAVR had a rise in their PEC when compared to baseline (0.19 ± 0.09 vs 0.14 ± 0.08 W, P = 0.04). Baseline PEC correlated moderately with baseline SEC (R = 0.49, P = 0.03), and a high baseline PEC was predictive of post TAVR PEC reduction (R = 0.54, P =0.01). Overall, no significant differences were found between baseline and post TAVR for systolic aortic pressure (131 ± 20 vs 131 ± 20 mmHg), systemic vascular resistance (1894 ± 493 vs 2015 ± 519 dynes.s/cm5), aortic valve ejection time (337 ± 22 vs 324 ± 34 ms) or aortic characteristic impedance (120 ± 48 vs 107 ± 41 dynes.s/cm5). Improved flow profiles after TAVR likely unmask the true vascular properties by altering ventriculo-valvulo-arterial coupling, leading to downstream vascular remodelling secondary to flow conditioning, and results in eventual improvement of pulsatile afterload as reflected by our proposed index of CAPE.

Enhanced Elman spike neural network for cluster head based energy aware routing in WSN

AbstractAn enhanced Elman spike neural network (EESNN) optimized with hybrid wild horse optimization and chameleon swarm algorithm is proposed in this manuscript for multi‐objective cluster head selection and energy aware routing in wireless sensor network (CH‐EESNN‐Hyb‐WH‐CSOA‐WSN). Initially, EESNN is used to intelligent selection of cluster head. Then, the optimal cluster head utilized the selected data transferring process with the consideration of multi‐objective fitness function based EESNN. Here, some of the multi‐objective fitness function factors are considered, like energy, delay, throughput, distance between the nodes, traffic rate and cluster density. The hybrid wild horse optimization and chameleon swarm algorithm (Hyb‐WH‐CSOA) is taken into account for the optimal route path selection with minimal delay. The proposed CH‐EESNN‐Hyb‐WH‐CSOA‐WSN method is activated in network simulator 3 (NS‐3) tool. The performance of the proposed method is examined under certain performance metrics, like count of alive nodes, drop, network lifetime, delay, throughput, energy consumption, and packet delivery ratio. Finally, the proposed method attains 98.78%, 97.21%, 99.61% lower delay, 98.78%, 99.21%, 96.78% higher delivery ratio, and 99.57%, 98.67%, 98.88% lower packet drop compared with the existing methods, like optimal secure cluster head placement through source coding techniques in wireless sensor networks (CHP‐HMC‐WSN), optimal placement of single cluster head in wireless sensor networks via clustering (CHP‐K‐Means C‐PSO‐WSN) and hybrid firefly approach along particle swarm optimization for energy efficient optimum cluster head selection in wireless sensor networks (CHP‐HFAPSO‐WSN) respectively.

TiO2 quantum dots: Energy consumption cost,germination, and phytotoxicity studies, recycling photo and solar catalytic processes of reactive yellow 145 dye and natural industrial wastewater

The germination of Lycopersicon esculentum tomato seeds that had been planted with water containing TiO2QDs1(2.9 nm), TiO2QDs2 (3.2 nm), and TiO2 (Degussa) without no phytotoxicity effect on the germination process. TiO2QDs1 (2.9 nm) and TiO2QDs2 (3.2) were successfully synthesized at low calcination temperatures: 280 and 310 0C for 180 min, respectively, using the sol–gel process. The synthesized TiO2QDs1(2.9 nm) and TiO2QDs2 (3.2 nm) were characterized by: XRD, FE-SEM, HRTEM, and EDX to analyze the structure, shape, and size of the generated TiO2QDs samples. The photocatalytic activities of the TiO2QDs in the photodegradation of Reactive yellow 145 dye as a commercial dye and actual industrial wastewater samples using both a Xenon lamp light irradiation source and direct sunlight were assessed. They showed highly photocatalytic performances recorded at 85 to 90 percent, and the photodegradation rate was still distinguishable till ten repetition times for the photodegradation process of the reactive yellow 145 dye and till six repetition times for the natural industrial wastewater samples used in this study. Also, an analysis of the photodegradation efficiency of the Reactive yellow 145 dye has been done in terms of the positive effect on the energy consumption ratio (EE/O) as pricing estimations.

Mutation Based Hybrid Routing Algorithm for Mobile Ad-hoc Networks

Mobile Adhoc NETworks (MANETs) usually present challenges such as a highly dynamic topology due to node mobility, route rediscovery process, and packet loss. This leads to low throughput, a lot of energy consumption, delay and low packet delivery ratio. In order to ensure that the route is not rediscovered over and over, multipath routing protocols such as Adhoc Multipath Distance Vector (AOMDV) is used in order to utilize the alternate routes. However, nodes that have low residual energy can die and add to the problem of disconnection of network and route rediscovery. This paper proposes a multipath routing algorithm based on AOMDV and genetic mutation. It takes into account residual energy, hop count, congestion and received signal strength for primary route selection. For secondary path selection it uses residual energy, hop count, congestion and received signal strength together with mutation. The simulation results show that the proposed algorithm gives better performance results compared to AOMDV by 11% for residual energy, 45% throughput, 3% packet delivery ratio, and 63% less delay.

Influence of cutting parameters and modes on coal fracture efficiency

The efficiency of the process of coal cutting by coal cutting machines depends, all other things being equal, on the method of coal fracture, characterized by the number and relative location of the exposed planes, as well as by the orientation of the main plane of the cutting tool relative to the fracture surface. With greater degree of exposure of the face surface, coal fracture is easier. In this regard, the article considers various types of cutting with characteristic cross-section shapes of chips, and assesses them from the point of view of the energy intensity of the process. The main operating parameters that determine efficiency of the coal cutting process are the thickness, width and cross-section of chips, the ratio of which governs the cutting energy intensity and productivity. The patterns of the influence of operating parameters on the force and energy parameters of the cutting process are considered. It is found that for almost all types of cutting, with increasing chip thickness, the energy intensity of cutting and the degree of coal fragmentation reduce along a hyperbola and stabilize at the chip thickness exceeding 3&ndash;5 cm. The theoretical chip width conditioned by the distance between the side faces of the cutter at the height of their contact with rock mass depends on the brittleness of coal, chip thickness, type of cutting, shape of the cutting edges and surfaces of the cutting part, cutting angles, as well as on the sharpening and setting of the cutter. The formulas for determining the theoretical values of the chip width for various designs of the cutting part of the cutters are given. The joint effect of the chip thickness and width on the specific energy consumption during cutting is estimated. To analyze and quantify the effect of operating parameters on energy consumption during cutting, the face exposure coefficient is proposed, which is the ratio of the specific energy consumption at the studied values of the chip thickness and width to the energy consumption in the reference cutting mode with the same chip thickness. The theoretical dependences are obtained for determining the optimal values of the face exposure coefficient and chip width during operation of shearers and ploughs. It is found that the feed rate and cutting speeds, as well as their ratio, practically have no influence on the loads on the cutters and, therefore, can be ignored in the calculations for choosing parameters of excavating machines.

A Stackelberg Game Theory Based Demand Response Algorithm for Domestic Consumers

A stackelberg game algorithm is proposed to optimize real time demand response equilibrium between consumers and utilities with the integration of renewable energy sources. Stackelberg game is played between one leader and N followers to provide interaction between utility and consumers in the presence of energy management center. The objective of consumers is to minimize their energy tariffs by scheduling their appliances. Appliances are categorized as non-shiftable, shiftable and curtailable appliances based on their applications. The objective of the utility is to maximize its profit by managing peak to average energy consumption ratio, penetration of renewable energy sources as a primary source and during peak hours, integrate electric vehicles as a backup. The existence of a unique stackelberg equilibrium that provides an optimal energy consumption scheme to each appliance at the consumer end was demonstrated. The simulation results showed the optimal real time demand response using stackelberg game algorithm is effective for achieving the optimal load control.

Experimental study on effect of drying air supply temperature on performance of a quasi-two-stage closed loop heat pump drying system for lentinus edodes

A new closed loop quasi-two-stage enhanced vapor injection heat pump drying system with high drying air supply temperature and simple structure was proposed and built. Firstly, the system operation characteristics including parameters of both heat pump refrigerant and air cycle sides were analyzed. The effects of different drying air supply temperatures on heat pump system drying performance and drying quality for Lentinus edodes were investigated experimentally. The results showed that the maximum drying air supply temperature in the designed system could reach 70 °C. As the drying air supply temperature raised from 40 °C to 70 °C, the drying rate of L. edodes was significantly increased, the average coefficient of performance of the system (COPsys), average specific moisture extraction rate (SMER) and rehydration ratio first increased and then decreased. The average COPsys, average SMER, drying amount per unit energy consumption and rehydration ratio reached the maximum values when the drying air supply temperature was 55 °C, which were 4.19, 0.320 kg/(kW·h), 0.391 kg/(kW·h) and 3.6, respectively. Compared with hot-air drying of L. edodes, the heat pump drying system proposed in this paper also had a significant improvement in the quality (the rehydration ratio increased by more than 45%).

Energy and load balancing routing protocol for IoT

SummaryDue to the limitation of node energy resources, the management of energy consumption is one of the most important problems of the internet of things (IoT). Therefore, many studies have tried to optimize and manage energy consumption by focusing on different techniques. Although each of these studies has improved and optimized energy consumption, there are many important problems, including maintaining traffic balance and energy consumption of network nodes. Therefore, a new method is necessary to maintain the load and energy balancing of network nodes. Therefore, this paper introduces energy and load balancing routing protocol for IoT (ELBRP) based on the development of the RPL routing protocol and the efficiency of data distribution technique. The ELBRP performance has three steps. In the first step, along with the process of sending DODAG information object (DIO) messages, the status of network nodes is evaluated. In the second step, the DODAG communication graph is formed according to the ELBRP. In the third step, data transmission is done according to the distribution technique with the goal of balancing traffic and energy. The simulation results using cooja simulator showed the superiority of ELBRP in improving energy consumption and successful delivery ratio, reducing delay and increasing the network lifetime compared to the similar methods.

Comparative Energy Consumption Structure and Mode between China and Major Energy-Consuming Countries Under the Background of Carbon Emission Reduction

The top 23 countries with energy consumption accounting for 80% of the worldwide total in 2020 were selected as the research objects for this study. The energy consumption structure of these countries has been compared and studied from the proportion of clean energy in primary energy, the clean utilization rate of fossil energy, and the proportion of electric energy in terminal energy consumption, and the characteristics of energy consumption intensity were also analyzed based on the energy consumption per unit GDP, capital, and unit land area. The energy consumption patterns of various countries in social-economic operation, production, and life were also discussed, combined with the characteristics of industrial structure and subsector energy consumption. The concept of natural carbon sink load ratio of energy consumption was put forward, and the advantages and challenges of energy consumption mode transformation under carbon peak and carbon neutralization goals in China were identified and analyzed. The results showed that:the proportion of clean energy in primary energy, the proportion of energy consumption for power generation, the clean utilization rate of fossil energy, and the proportion of electric energy in terminal energy consumption in China were 15.90%, 53.48%, 37.51%, and 26.54%,respectively,all of which were in the forefront among the major energy-consuming countries in the world. China has built a favorable structural foundation for energy-intensive and clean utilization and formed a green and low-carbon energy consumption model; the proportion of non-industrial and agricultural energy consumption, especially that of transportation energy consumption, were both the lowest among major energy-consuming countries, and there is still much room for improvement in overall energy productivity based on the optimization of industrial structure. However, the relatively short carbon peak and neutralization target period poses a great challenge to the development speed and scale of clean energy to China, and the international situation under the constraint of carbon emission also increases the difficulty for China to achieve the carbon reduction goal by optimizing and adjusting the industrial structure.

Numerical optimization of guaco leaves extraction based on pre‐heat treatment

AbstractThe mass yield of the extraction is influenced directly by the pre‐treatment conditions of the raw material. In the case of leaves, drying is required to ensure their biological stability and is a pre‐processing step that demands large amounts of thermal energy. In the present study, the oil extraction process was numerically optimized, considering the influence of the pre‐heat treatment of the guaco leaves. An operating range between 30°C and 70°C, 1.0 and 5.0 m/s, and recirculation between 0 and 1 was evaluated. The minimum ratio of energy consumption of drying by the amount of oil obtained after extraction (4.05 × 105 kWh/kg) was obtained under the optimal conditions of 30.02°C, 1.0 m/s, and .129 of air recycling flow rate. With our results, it is possible to guarantee safety in the storage of guaco leaves, in addition to optimizing the extraction process, maximizing the obtaining of the oil mass, and reducing energy consumption in the drying step.Practical applicationsTea is one of the most consumed beverages in the world and is obtained by extraction. Between tea leaves, guaco (Mikania glomerata Sprengel) is mainly applied to obtain therapeutic properties as an expectorant and bronchodilator. While guaco leaves are perishable, they must be dried to ensure their biological stability. As others heat and mass transfer processes, the efficient design is mandatory to reduce energy consumption. One of the more efficient drying processes is the operation under exhaust air recirculation. Thus, there is a need to evaluate optimal drying operation conditions to understand the effects of exhaust air recirculation on the energy consumption of drying and the amount of extract obtained in the extraction. Our numerical results indicated that it is possible to guarantee safety in storing guaco leaves and optimize its extraction process.

Energy-Efficient Guiding-Network-Based Routing for Underwater Wireless Sensor Networks

With the increasing underwater applications, underwater wireless sensor networks (UWSNs) have become a research hotspot. Routing protocols used to keep network connectivity and reliable transmission are essential in UWSNs. Due to the specific limitations in UWSNs, such as serious ocean interference, high propagation latency, and dynamic network topology, it is challenging to balance multiple performances, such as real timeness and energy efficiency in a routing protocol. To this end, this article proposes a localization-free routing scheme, termed energy-efficient guiding-network-based routing (EEGNBR) protocol, to provide a time saving and reliable routing for UWSNs, which is a good choice for applications characterized by intermittent connectivity. For reducing the network delay, EEGNBR cites the advantageous distance-vector mechanism and establishes a guiding network to provide underwater sensor nodes with the shortest route (minimum hop counts) toward the sinks. Moreover, EEGNBR innovatively replaces the waiting mechanism used in traditional opportunistic routing with a novel data forwarding mechanism named concurrent working mechanism, which could greatly reduce the forwarding delay while guaranteeing reliable routing. In order to ensure routing reliability as well as avoid duplicate transmission, the forwarding protection mechanism is adopted to save energy consumption and extend the service life of the network. Simulation results show that EEGNBR performs significantly better than some classical related protocols in terms of network delay while maintaining comparable or even better energy consumption and packet delivery ratio.

Effect of particle regularity on the shear response of geogrid-granular material interface under cyclic normal loading

The investigation of shear behaviour on geogrid-granular material interface under cyclic normal loading (CNL) is significant in seismic design of reinforcement structure. The cyclic shear mechanism about the effect of particle overall regularity on reinforced soil interface was analysed using dynamic direct shear apparatus. Five mixtures of round spherical media and crushed limestone with different percentages were selected to obtain various particle overall regularity. By comparing the shear behaviour under various overall regularity, the interface shear stress and vertical displacement under the CNL condition were smaller than those under the static loading condition. The decrement in interface shear stress of lower overall regularity was smaller than that of higher overall regularity. The interface peak shear stress, final vertical displacement decreased with the increase of cyclic normal loading amplitude and overall regularity. The effect of initial normal loading on ratio of strength reduction and energy consumption was reverse to that of the overall regularity. Based on the constant relative phase shift of the peak normal stress and friction coefficient for various overall regularity, the prediction formula was proposed. The test results improve the understanding on how normal loading perturbations and particle overall regularity affect the shear behaviour of reinforced soil interface.

GVMP: A multi-objective joint VM and vGPU placement heuristic for API remoting-based GPU virtualization and disaggregation in cloud data centers

The diverse needs of customers drive cloud providers to incorporate more GPU-enabled services. It is known that users barely utilize GPUs. Hence, GPU virtualization techniques are employed to enable GPU sharing and increase resource utilization. Among GPU virtualization techniques, API remoting leverages disaggregation for GPU provisioning, allowing GPUs to be accessed remotely by non-resident VMs. It enables a VM to access any available GPU in the data center which, in turn, provides more flexibility to reach a better placement. It also enables users to choose VM and vGPU instances separately based on computational needs as GPU-enabled VM instances with fixed configurations may not proportionally utilize allocated resources. However, an inefficient VM or vGPU placement may result in poor performance and increase in energy consumption and rejection ratio. There is also a network communication overhead for remotely allocated vGPUs. The main challenge is how to place VMs and vGPUs such that rejection ratio is decreased and the negative performance impacts caused by GPU sharing and remote access are kept at a minimum. In this work, we formally define the joint problem of VM and vGPU placement based on API remoting as a multi-objective ILP model and introduce gVMP as a heuristic to solve it. The proposed method is compared against state-of-the-art heuristics and commercial solutions that are based on API remoting and GRID technologies for the placement of GPU-enabled VMs. We study the effectiveness of the proposed gVMP algorithm for low and high arrival rates in slow and fast networks. Our results show that under different scenarios and in comparison to state-of-the-art policies, our heuristic improves average request duration, efficiency, and SLA by up to 40%, 25% and 29%, respectively.

The puzzle of energy efficiency in Turkey: combining a multiple criteria decision making and the time series analysis

ABSTRACT Enhancing energy efficiency is important for sustainable economic development and environmental-related issues such as carbon emissions. Therefore, measuring energy efficiency is crucial for countries to achieve economic and environmental objectives. In this study, we utilize the TOPSIS method with the intent of monitoring the energy efficiency of Turkey from the 1980 to 2018 period. Several variables such as renewable and nonrenewable energy consumption, GDP, labor force, and capital stock are employed in calculating energy efficiency scores. Thereafter, we analyze the long-term, symmetric and asymmetric effects of some contextual variables such as capital stock-labor force ratio, renewable energy consumption-total energy consumption ratio, and carbon emission-total energy consumption ratio on energy efficiency via ARDL and nonlinear ARDL models. Results from the linear model indicate that an increase in the renewable energy consumption-total energy consumption ratio and capital stock-labor force ratio increase the energy efficiency. In contrast, an increase in the carbon emission-total energy consumption ratio decreases it. The nonlinear ARDL model, on the other hand, signals asymmetric effects in the long-run but not in the short-run.

A Secure LEACH Protocol for Efficient CH Selection and Secure Data Communication in WSNs

Due to the applications of wireless sensor networks (WSNs) in distinct fields, like civilian and military, environmental monitoring, and target tracking, etc., it became the important research area for researchers. Therefore, an efficient organization of network topology is needed for multi-hop data aggregation based on the energy constrained WSNs with large scale deployment for making the routing task simpler, balancing the load efficiently, and enhancing the network lifetime. The low-energy adaptive clustering hierarchy (LEACH) is an architecture of application-specific protocol, which is used for WSNs. However, this LEACH protocol suffered from more energy consumption in network without considering the cluster heads (CHs) distribution on a rotation basis. In addition, the complex security mechanisms are not sufficient due to limited bandwidth and other restrictions that the sensor nodes have. Thus, it is essential to improve the energy efficiency, CH stability and secure data transmission in WSN’s, which is the main objective of this work. Motivated from these three challenges, this article proposes a stable and secure LEACH (SS-LEACH), in which a new and improved protocol of LEACH is proposed for enhancing the stability of CH and energy efficiency as it considers the nodes’ consumed energy ratio (CER) for CH selection and random number generation, here after the proposed LEACH is named as CER-LEACH. In addition, it aims to prevent the previously elected CH node and it will get another chance in the current round. This method correlates the threshold used in traditional LEACH with the energy consumption ratio of each node. Further, it also introduces a hybrid reputation-based data transmission (HRDT) scheme for secure data transmission. With the proposed CER-LEACH protocol, WSNs achieves better performance in terms of secured communication, network lifetime, and energy consumption based on the analysis of simulation results as compared to state-of-art approaches.

Numerical simulation of heat pump drying system for paper exhaust hood

Abstract In view of the present situation that the exhaust waste heat of the hot air hood in the paper drying section is too much and the environment is not friendly, a closed heat pump drying system model applied to the exhaust air hood is proposed and established. Effects of evaporation temperature and condensation temperature on supply air temperature, supply air moisture content, system performance coefficient (COP) and dehumidification energy consumption ratio (SMER) were studied. Results show that with the increase of condensation temperature, the supply air temperature is unchanged, and the moisture content of the supply air increase, while the COP and SMER of the system show a downward trend. The moisture content of supply air decrease with the increase of evaporation temperature, while the supply air temperature, COP and SMER all show an upward trend. Therefore, in order to improve the drying characteristics and improve the performance of the heat pump system, the condensation temperature can be reduced and the evaporation temperature can be increased.

Optimal Design of Failure Mode Control for Semi-rigid Steel Frame Based on Elitist Retained Genetic Algorithm

The post-earthquake reports show that failure mode control design is of great significance to improve the seismic performance of structures. To realize the optimal design of failure mode in semi-rigid steel frame, a failure mode optimisation design method based on an elite retained genetic algorithm was developed in this study. Firstly, a database of 96 extended end-plate connections was established using the ABAQUS finite element software to obtain the initial rotational stiffness and yield moment under failure criteria. Secondly, with section size as the optimisation variable, failure mode as the constraint condition, and total steel consumption as the objective function, elite gene transfer was realized through gene sequence replication, hybridisation and mutation. With a 10-story, 3-span, semi-rigid steel frame as an example is proposed to demonstrate the application of the proposed semi-rigid design method, and pushover and time history analyses were conducted on the optimized results to verify the accuracy of the proposed method. The analysis results showed that the stable and reliable optimal design results were obtained through 1317 generation genetic iterative calculations, and the energy consumption ratio of the semi-rigid connection (including the beam ends) was 95.82% and that of the column was 4.18%; in addition, 76% of the beam ends had plastic hinges to dissipate energy in the pushover analysis. This finding indicates that the optimized frame can achieve the global failure mode during earthquakes, and the design method can effectively improve the seismic performance of the frame.

Production of animal feed from food waste or corn? Analyses of energy and exergy

The aim of the study was to investigate the energy and exergy consumption of the food waste dryer and then to compare the energy required to produce animal feed with the waste drying method and conventional methods. The required waste from the kitchens has been collected so that each collection period was considered as a block due to having different moisture content. The results showed that the amount of energy consumed increased along with increasing temperature to 29.23 kJ, also wasted exergy and the rate of recovery was significantly increased, but the efficiency of the device decreased significantly. Over time, energy consumption, energy consumption ratio, improvement potential rate have increased, but exergy efficiency reduced. Obtained results suggest that the conversion of food waste into animal feed requires 1.8 MJ per kg less energy. Finally, feed production from food waste is more affordable than agriculture because not only we need less energy than but also we don't spend money to get initial materials.