Mean Energy Consumption Research Articles

A tool for time, variance and energy related performance estimations in a shuttle-based storage and retrieval system

• The mean and variance of travel time of lifts and shuttles are estimated well. • The mean energy consumption and energy regeneration per transaction are estimated. • By the provided tool, such systems’ performances can be calculated promptly. • It is the first time such an analytical-based tool for an SBS/RS is studied. • The results are highly accurate (1% APE) when compared with the simulation results. The aim of this study is to present a tool that can calculate critical performance measures of different Shuttle-Based Storage and Retrieval System (SBS/RS) designs. Specifically, our aim is to develop an analytical model-based tool that can estimate the mean and variance of travel time of lifts and shuttles, as well as the mean amount of energy consumption and energy regeneration per transaction for a pre-defined SBS/RS design. The methodology illustrated in this paper can also be utilized for any system having a straight discrete travel pattern with equal distance stop points. We are motivated in this study by a relatively new automated storage and retrieval technology, SBS/RS. By the provided tool, one can evaluate these systems’ performance promptly by changing the input design parameters (e.g., discrete travel lengths, velocity of vehicles, acceleration/deceleration of vehicles, number of tiers, number of bays, etc.) of these systems. The analytical models used in the tool are verified via simulation for several SBS/RS design scenarios. As a result, it is found that the proposed tool produces highly accurate results, specifically less than 1% Absolute Percentage Error from the simulation results.

An IoT based modified graph cut segmentation with optimized adaptive connectivity and shape priors

Internet of Things (IoT) is the network of physical objects embedded with software, electronics, sensors and network connectivity which enables these objects to collect and exchange data. IoT based image processing is reaching up to a different level which is becoming a major part of everyone life. IoT based image segmentation is used to solve the real world problems like animal classification in wildlife monitoring and vehicle classification etc. Image segmentation is one of the processes of image processing technique which involves partitioning an image into multiple segments so that any region of interest can be obtained easily. The modified graph cut approach is one of the image segmentation techniques that avoid the boundary and region balance problem of graph cut technique by removing the regional term and strengthening the boundary term with the prior information. By combining shape priors in an adaptive way, a robust way to harness the shape prior was introduced in graphcut segmentation that reduced the memory size required for modified graph cut implementation. However, the structural regularities were not handled by the modified graph cut with adaptive shape prior method. Hence, in this proposed work the structural irregularities in image shapes are considered for image segmentation where the connectivity constraints are formulated such that corresponding optimization problems are all NP-hard which is solved by optimized DijkstraGC and problem decomposition approach. The segmentation with satisfied constraint results in an efficient image segmentation which reduces amount of time required for segmentation process. Furthermore, parameter of adaptive shape prior and connectivity constraints are optimized using BAT algorithm to improve the performance of image segmentation. Results clearly shows that proposed approach gives better results in terms of Root Mean Square, Energy Consumption and correlation coefficient.

Smart indoor humidity and condensation control in the spring in hot-humid areas

Continuous wet weather occurring in the spring in hot-humid areas causes many inconveniences and discomfort for building occupants. Techniques that control indoor environments well under continuous wet weather are still lacking. A smart, indoor humidity and condensation control logic was proposed based on condensation prevention logic and the adaptations of local people in hot-humid areas. The smart control system was established, and the field test was conducted in an office building in Guangzhou, China, during typical continuous wet weather in 2017. The test confirmed that the expected targets were successfully achieved by the control system with a fault rate of 5%. Compared to the conventional control (dehumidifiers always running and windows freely opened), under the smart control, the indoor air temperature and MRT increased by 0.6–2.1 °C and 0.4–2.1 °C, respectively; the indoor relative humidity and CO2 concentration were similar; the occupants perceived the indoor environment as slightly cooler and wetter and as acceptable in terms of the thermal environment, humidity and air quality; and the daily mean energy consumption on regulating the environment decreased by 90%. The smart control shows great advantages for energy savings by proposing the control logic based on the adaptations of local people, integrating operable windows with dehumidifiers, and fully utilizing natural heat sources.

Cooling and heating energy performance of a building with a variety of roof designs; the effects of future weather data in a cold climate

Building engineers commonly use the Typical Meteorological Year (TMY) weather data for simulation and design purposes. However, the nature of TMY in excluding weather extremes makes them less suitable to investigate the effect of potential climate change on building design as climate change likely increases the frequency and magnitude of those extreme conditions. The current practice of designing buildings has lacked a clear method to incorporate future climate change trends. An approach is used to compare present weather simulation results of a commercial building with varying roof reflectance and insulation thermal resistance parameters with future year-by-year results which are affected by potential climate change. Future weather data for year-by-year simulations is obtained by “morphing” historical weather data with a General Circulation Model (HadCM3). Mean energy consumption and optimal roof configurations are discussed with regards to climate change over the study period, and are compared to results obtained with TMY data. Results show that increased roof solar reflectance always lead to less mean and less variant cooling energy consumption. The study shows the importance of considering possible future climate scenarios and in building energy performance design.

Energy-Delay Tradeoff in Ultra-Dense Networks Considering BS Sleeping and Cell Association

Ultra-dense network (UDN) is a promising technology for future wireless networks to meet the explosively increasing wireless traffic demands. Sleeping strategy that switches base station (BS) on/off to reduce the energy consumption of UDN is widely investigated. However, the energy saving of sleeping strategy may come at the cost of increased delay. Hence, energy-delay tradeoff (EDT) which means how much energy can be saved by trading off tolerable delay is an important topic. In this paper, we develop a theoretical framework for EDT considering BS sleeping and cell association in UDNs. Firstly, an M/G/1/N processor sharing vacation queueing is introduced to model small cell considering sleeping strategy and cell association. Mean delay and energy consumption are quantitatively studied based on the queueing model. The general expressions for mean delay and energy consumption are derived. It shows that sacrificing delay will not always bring about energy saving. Then, EDT problem is formulated as a cost minimization problem, and the optimal sleeping time and association radius are investigated to achieve the optimal tradeoff between energy consumption and delay. Since there is no closed-form expression for the optimal sleeping time for arbitrary number of users associating with one small cell, the optimal sleeping time for one and infinite number of users are derived. Simulation results demonstrate that the optimal sleeping time for infinite number of users is a reasonable approximation for arbitrary number when it is more than one.

Performance Analysis of Priority-Based IEEE 802.15.6 Protocol in Saturated Traffic Conditions

Recent advancement in internet of medical things has enabled deployment of miniaturized, intelligent, and low-power medical devices in, on, or around a human body for unobtrusive and remote health monitoring. The IEEE 802.15.6 standard facilitates such monitoring by enabling low-power and reliable wireless communication between the medical devices. The IEEE 802.15.6 standard employs a carrier sense multiple access with collision avoidance protocol for resource allocation. It utilizes a priority-based backoff procedure by adjusting the contention window bounds of devices according to user requirements. As the performance of this protocol is considerably affected when the number of devices increases, we propose an accurate analytical model to estimate the saturation throughput, mean energy consumption, and mean delay over the number of devices. We assume an error-prone channel with saturated traffic conditions. We determine the optimal performance bounds for a fixed number of devices in different priority classes with different values of bit error ratio. We conclude that high-priority devices obtain quick and reliable access to the error-prone channel compared to low-priority devices. The proposed model is validated through extensive simulations. The performance bounds obtained in our analysis can be used to understand the tradeoffs between different priority levels and network performance.

MANAGEMENT OF CHEESE WHEY BY FILM FREEZE CONCENTRATION

This study evaluates the behavior of freeze concentration of cheese whey (CW). Parameters studied were: Chemical Oxygen Demand (COD), Total Dissolved Solids (TDS), Suspended Solids (SS), Total Settleable Solids (TSS), pH and electrical conductivity (EC) in the concentrated cheese whey and in the ice. The final concentration of TDS reached was 25 0.16 %wt for the liquid phase, which corresponds to a reduction of 83% of the initial volume. The COD in the ice fractions had lower values than the COD in the original cheese whey. The mean energy consumption was of 0.25 kWh/kg of ice. The results indicate that low levels of fat and low levels of salt in cheese whey improve the efficiency of the process of freeze concentration and reduce the environmental impact.

Modified energy minimization scheme using queue threshold based on priority queueing model

A wireless sensor network (WSN) is a group of specialized sensor nodes with a communication infrastructure intended to monitor and record conditions at diverse locations. The critical issue in WSNs is represented by the limited availability of energy within the network and hence optimizing energy consumption is very important. One important existing technique used to prolong the network lifetime of WSN is the Energy Minimization Scheme (EMS) using N-Policy Model (NPM) based on queue threshold but this technique increases mean delay. This paper proposes a Modified Energy Minimization Scheme (MEMS) which reduces the mean delay and average energy consumption of individual nodes in the cluster based heterogeneous sensor network using queue threshold based on M/D/1 Priority Queueing Model (PQM) in order to prolong the network lifetime. The expression for the optimal value of queue threshold for which the node consumes minimum energy using PQM is also derived. Results show that the mean delay is highly reduced in PQM when compared to the NPM and the trade-off exist between the average energy consumption and mean delay is explored. We perform simulations and the results obtained show that the simulation results match with the analytical results thus validating the accuracy of the approach.

The free-energy cost of interaction between DNA loops

From the viewpoint of thermodynamics, the formation of DNA loops and the interaction between them, which are all non-equilibrium processes, result in the change of free energy, affecting gene expression and further cell-to-cell variability as observed experimentally. However, how these processes dissipate free energy remains largely unclear. Here, by analyzing a mechanic model that maps three fundamental topologies of two interacting DNA loops into a 4-state model of gene transcription, we first show that a longer DNA loop needs more mean free energy consumption. Then, independent of the type of interacting two DNA loops (nested, side-by-side or alternating), the promotion between them always consumes less mean free energy whereas the suppression dissipates more mean free energy. More interestingly, we find that in contrast to the mechanism of direct looping between promoter and enhancer, the facilitated-tracking mechanism dissipates less mean free energy but enhances the mean mRNA expression, justifying the facilitated-tracking hypothesis, a long-standing debate in biology. Based on minimal energy principle, we thus speculate that organisms would utilize the mechanisms of loop-loop promotion and facilitated tracking to survive in complex environments. Our studies provide insights into the understanding of gene expression regulation mechanism from the view of energy consumption.

Socioeconomic differences in diet composition of the adult population in southern Brazil: a population-based study

To describe the intake of macro- and micronutrients, verify its adequacy, and analyze their distribution by the socioeconomic and demographic profile of adults. Longitudinal population-based study with a sample of 1222 people aged 22–63 years from Florianopolis, Southern Brazil. The dietary intake data were collected with a 24-h recall in the total sample, plus a second recall applied on a sub-sample of participants with subsequent adjustment of regular consumption. Diet composition and adequacy of intake were compared between the different educational groups and stratified by sex. The mean energy consumption was 1851 Kcal [standard error (SE) = 15.0 Kcal] and 2259 Kcal (SE = 27.8 Kcal) in females and males, respectively (p-value <0.001). With increasing education, women showed an increasing trend in energy consumption, carbohydrates, proteins, lipids, saturated, polyunsaturated and monounsaturated fat, cholesterol, and fiber. In men, the same differences were found only in saturated fat and cholesterol (p-value <0.05 for all). Analyzing the adequate consumption of nutrients, differences were found regarding saturated fat and cholesterol in women and carbohydrates, saturated and polyunsaturated fat in men. The prevalence of inadequacy was up to 47% comparing the different educational groups. A lower percentage of adequacies in food consumption was found in both sexes for those with more years of schooling. Public policy should also target the group with higher education.

Comparison of Experimental Designs Used to Study Variables during Hammer Milling of Corn Bran

<abstract> <b><sc>Abstract.</sc></b> Corn bran at three moisture contents (6%, 13%, and 24% d.b.) and feed rates (11.89, 23.86, and 35.86 g s^-1) was ground using a hammer mill operated at two different tip speeds (19.0 and 47.0 m s^-1). Geometric mean diameter (GMD) and energy consumption were observed within a split-plot experimental design. Additionally, the statistical precision of the split-plot experimental design was compared to the statistical precision of the experiment if it had been conducted as a randomized complete block design (RCBD) with a factorial treatment structure. Moisture content (MC) had a significant effect on GMD (final particle size) but not on energy consumption. Tip speed (TPS) had significant effects on both GMD and energy consumption. Feed rate (FR) had a significant effect on energy consumption but no significant effect on GMD of corn bran. Energy consumption was observed to increase with increasing TPS and FR. Conducting the experiment as a split-plot design substantially increased the precision for energy consumption with regard to FR and TPS, whereas the precision for MC was decreased when compared to an RCBD. Particle size GMD precision was only slightly affected by using a split-plot design as compared to conducting the experiment as an RCBD. Finally, if hard-to-change (HTC) and easy-to-change (ETC) factors exist, it is important to consider different-sized experimental units. Neglecting to consider this issue can result in inefficient use of resources and possibly lead to inaccurate and biased results.

Modelling green HetNets in dynamic ultra large-scale applications: A case-study for femtocells in smart-cities

In recent years, with the rapid increase in the number of mobile connected devices and data traffic, mobile operators have been trying to find solutions to provide better coverage and capacity for mobile users. In this respect, deployment of femtocells is a promising solution. This paper presents performability analysis of femtocells. Unlike the existing studies, the potential reduction of the service capacity due to failures are considered as well as various performance metrics such as throughput, mean queue length, response time, and energy consumption. In other words, the femtocells are modelled as fault tolerant wireless communication systems, considering factors such as mobility of the mobile users, multiple channels for the femtocells, and failure/repair behaviour of the channels for more realistic performance measures. A typical scenario is considered for smart-city applications as case study where a set of femtocells are deployed within the coverage area of a macrocell. The numerical results presented show the accuracy of the proposed model as an abstraction of a femtocell system. The results also reveal that the computational efficiency of the analytical model is significantly better than simulation.

Adaptation-based indoor environment control in a hot-humid area

Human thermal adaptation has received more and more attentions since 1990s as its capability to explain and predict human thermal comfort in buildings. The present study aimed to propose a new indoor environment control based on human thermal adaptation (named as adaptation-based control), and test its performance in the hot-humid area. The adaptation-based control was defined as the united control of operable windows, electric fans and air-conditioners by sensing indoor and outdoor environment parameters with an aim to creating a healthy, comfortable and energy efficient indoor environment. The adaptation-based control system was set up and the field tests were conducted in an office building in the typical summer days. The tests confirmed that all the expected targets on indoor environment were well achieved by the control system. Compared to the conventional control (air temperature set point at 26 °C), the adaptation-based control increased the indoor air temperature, mean radiant temperature, moisture content and air speed while decreased the indoor CO2 concentration. The occupants perceived the indoor environment more close to neutral in thermal and humid aspects, and the same or more comfortable and acceptable in terms of thermal environment and air quality. The sick building syndrome incidence was decreased by 40%. The daily mean energy consumption on indoor air conditioning was saved by 31% on the sunny days and by 40% on the overcast days. The adaptation-based control is strongly recommended to apply in the hot-humid area as its great advantages on human comfort and energy saving.

E3TX: an energy-efficient expected transmission count routing decision strategy for wireless sensor networks

The routing protocol is one of the most important aspects of the wireless sensor network, determining network connectivity, delay, energy balancing, reliability and other factors. Furthermore, a minimum hop-count does not mean minimum delay and energy consumption. To overcome the routing protocol's shortcomings, we proposed an energy-efficient expected transmission count routing decision strategy (E3TX) for wireless sensor networks. E3TX makes use of two physical parameters, received signal strength indicator (RSSI) and battery voltage, to obtain the final decision via our proposed decision strategy. In our strategy, the received signal strength indicator is used to predict the future packet reception rate (PRR), and the battery voltage is used to estimate the residual energy of network nodes to balance their load. In order to estimate the packet reception rate via the received signal strength indicator with greater accuracy, we performed multiple experiments to build the relationship model between RSSI and PRR. In this article, we use NS-2.35 to evaluate and compare the performance of E3TX with AODV, AOMDV and BIETX. Our simulation results show that our proposed E3TX performs well when compared to the previous studies, not only in terms of energy consumption, but also in reliable data transmission and end-to-end delay.

A hybrid method of LMDI, symmetrical components, and SFA to estimate the distribution of energy-saving potential with consideration of unbalanced components in decomposition analysis

This paper proposes a hybrid method of logarithmic mean divisia index (LMDI), symmetrical components (SC), and stochastic frontier analysis (SFA) to estimate the distribution of energy-saving potential in industrial sectors, while taking into consideration unbalanced components in decomposition analysis. The proposed method uses LMDI to decompose actual energy consumption into activity, structural, and intensity factors, which serve as inputs to SC. In general the results of the decomposition analysis contain some degree of imbalance. The imbalance between these factors may affect economic development of industrial sectors. Since LMDI cannot be used for analyzing the unbalance, SC is used to analyze this. According to this technique, any set of three unbalanced factors could be expressed as the sum of three symmetrical sets of balanced factors. In this research, activity, structural, and intensity factors are selected as unbalanced components. Also, the mean energy consumption is estimated using SC. In this study, SFA is used to measure the technical efficiency of energy conversion in industrial sectors. Therefore, a feasible stochastic frontier production function, which requires only the actual consumption as input and the estimated mean consumption (output from SC) as output, is estimated. Finally, potential savings in these sectors are calculated as technical efficiency. The proposed method is validated by its application to estimate the distribution of energy-saving potential of the selected group of Canadian industrial sectors. The outcome of this study will assist policymakers in reducing industrial energy consumption.

A survey of feeding, activity, supplement use and energy consumption in North American agility dogs.

A survey was designed and administered at eighteen agility competitions across the Northeast and Midwest USA in 2015 to obtain information regarding competition level, training, feeding practices, owner-reported weight, body condition score (BCS) and supplement use. Average energy intake per d from reported consumption was assessed for all dogs in ideal body condition based on manufacturers' or US Department of Agriculture database information. To assess the respective parameters across competition levels (novice, open, master/elite), non-parametric or parametric ANOVA or χ2 was used to determine significance. There were 494 respondents with usable data. Results showed that approximately 99 % of respondents used treats and 62 % utilised supplements. Of the respondents, 61 % fed primarily commercial dry food. Approximately 25 % of owners fed foods other than commercial dry (i.e. raw/home-prepared or freeze-dried). This 25 % of non-traditional diets included: 11 % home-prepared raw/cooked diets, 11 % commercial raw/cooked diets, and the remaining 3 % were fed commercial freeze-dried raw products. The remaining 14 % fed a mix of commercial dry food and raw/home-cooked blend. Average BCS was 4·7 (sd 1·1). Mean energy consumption of 238 dogs (BCS 4-5/9) was 444 (sd 138) kJ/kg body weight0·75 per d (106 (sd 33) kcal/kg body weight0·75 per d), with no significant differences observed between dogs at different levels of competition. The mean percentage of energy from treats was 15·1 (sd 12·7) % of overall energy consumption.

Improvement of aqueous nitrate removal by using continuous electrocoagulation/electroflotation unit with vertical monopolar electrodes

Summary The present study is to investigate removal of nitrate from water solutions by the Electro-Coagulation-Flotation (ECF) process in continuous operation under different conditions. Experimental results indicated that the maximum nitrate removal was achieved by aluminum–aluminum electrode arrangement as anode–cathode. The increase in current density from 0.4 to 3.2 mA cm−2 increased nitrate removal efficiency from 55 to 96% under optimum conditions of time and pH during the ECF. Continuous operation of the ECF reactor led to an increase of nitrate removal from 37% at a detention time of 10 min–96% at a detention time of 30 min. Mean energy consumption and current efficiency were found to be about 2.66 kWh g−1 NO3− and 160%, respectively.

A building’s thermal assessment using dynamic simulation

A thermal analysis of a two-storey building was made using a dynamic simulation software (TRNSYS). Thermal performance of a 2000 m2 building was examined by means of several dynamic simulations. The building is located in a region within the BS climate (steppe) according to the Köppen climate classification, where both air cooling and heating are needed to provide comfortable thermal conditions through the entire year. This weather often represents an energy saving challenge, where heat gains and heat losses need to be efficiently managed. A selection of common construction and glazing materials was implemented, and a simple but effective ventilating strategy was tested. Six thermal zones were defined in the building and a comfort temperature range was established as an operating parameter. The results show hourly mean temperatures and energy consumption due to air conditioning throughout a year.

An Adaptive Transmission Scheme for Amplify-and-Forward Relaying Networks

In this paper, an adaptive scheme for amplify-and-forward relaying networks is proposed, which selects a certain transmission mode for each communication process. Depending on the instantaneous channel conditions, one of the following modes is selected: direct transmission with no cooperation, cooperative transmission with half-duplex relaying and maximal-ratio combining at the destination, or cooperative transmission with full-duplex relaying and maximal-ratio combining at the destination. A three-node network is considered, containing a single-antenna source, a two-antenna relay that is able to implement full-duplex communication, and a single-antenna destination. Energy normalization per block is assumed, so that in those modes using cooperation, the system’s transmission power is shared between source and relay. The performance analysis is provided in terms of outage probability and energy efficiency. We derive a tight approximate expression in closed form for the outage probability and an approximate expression in integral form for the mean energy consumption. The results show that our scheme outperforms all of transmission modes separately in terms of outage probability, while being more energy efficient than the cooperative transmission modes. In addition, the asymptotic analysis proves that the proposed scheme achieves full diversity order equal to 2, thus outperforming those schemes with direct transmission or full-duplex cooperation only.

Net energy analysis of Bakken crude oil production using a well-level engineering-based model

Since 2005, production of oil from the Bakken formation of North Dakota has increased substantially, and the region now supplies about 1.5% of global oil output. This study presents a first engineering-based assessment of the energy intensity of Bakken crude oil production and computes the resulting NER (net energy return) from Bakken hydrocarbon production. The energy required to drill, produce, and process Bakken oil and gas is estimated for over 7000 wells using open-source drilling and production assessment models. The largest energy uses are from drilling and processing of produced fluids (crude/water emulsions and gas). Fluid lifting and injection and embodied energy are also important energy needs. Median energy consumption equals ≈3.4% of net crude and gas energy content, while mean energy consumption equals ≈3.9% of hydrocarbon energy. The median NER is 29.3 MJ/MJ. The interquartile range is 24.3–35.7 MJ/MJ, while the 5%–95% range is 13.3–52.0 MJ/MJ. NERs have declined in recent years, with a decline in median NER of 23% between 2010 and 2014. Results are most sensitive to modeled estimated ultimate recovery, and embodied energy.