This study investigates a measurement method of thermal diffusivity for samples with arbitrary geometries and unknown material properties. The aim is to curve fit the thermal diffusivity with the use of a numerical simulation and transient temperature measurement inside the object of interest. This approach is designed to assess bulk material properties of an object that has a composite material structure such as underground soil. The method creates the boundary conditions necessary to apply analytical theory found in the literature. It was found that measurements best correlated with theory and simulation at positions between the center and surface of an object.

Properly selected tillage methods and management of the available organic matter resources are considered important measures to enable farming in accordance with the principles of sustainable agriculture. Depending on the depth and intensity of cultivation, tillage practices affect soil chemical composition, structure and biological activity. The three-year experiment was performed on the soil under spring wheat (cv. Tybalt) short-time cultivation. The influence of different tillage systems and stubble management on the soil’s chemical and biological parameters was analyzed. Organic carbon content (OC); content of biologically available phosphorus (Pa), potassium (Ka), and magnesium (Mg); content of total nitrogen (TN), mineral nitrogen forms: N-NO3 and N-NH4 were determined in various soil samples. Moreover, the total number of microorganisms (TNM), bacteria (B), actinobacteria (A), fungi (F); soil respiratory activity (SR); and pH in 1 M KCl (pH) were also investigated. The results s... [more]

In order to realize the intelligent management of a power materials warehouse, the Internet of Things based on wireless sensor networks (WSNs) is a promising effective solution. Considering the limited battery capacity of sensor nodes, the optimization of the topology control and the determination of the amount of collected data are critical for prolonging the survival time of WSNs and increasing the satisfaction of the warehouse supplier. Therefore, in this paper, an optimization problem on sensor association and acquisition data satisfaction is proposed, and the subproblem of the sensor association is modeled as the knapsack problem. To cope with it, the block coordinate descent method is used to obtain the suboptimal solution. A sensor association scheme based on the ant colony algorithm (ACO) is proposed, and the upper and lower bounds of this optimization problem are also obtained. After this, a cluster head selection algorithm is given to find the optimal cluster head. Finally, t... [more]

In this paper, a novel neural network-based robust control method is presented for a vehicle-oriented problem, in which the main goal is to ensure stable motion of the vehicle under critical circumstances. The proposed method can be divided into two main steps. In the first step, the model matching algorithm is proposed, which can adjust the nonlinear dynamics of the controlled system to a nominal, linear model. The aim of model matching is to eliminate the effects of the nonlinearities and uncertainties of the system to increase the performances of the closed-loop system. The model matching process results in an additional control input, which is computed by a neural network during the operation of the control system. Furthermore, in the second step, a robust H∞ is designed, which has double purposes: to handle the fitting error of the neural network and ensure the accurate tracking of the reference signal. The operation and efficiency of the proposed control algorithm are investigate... [more]

The aim of this paper is to present a model of energy efficient scheduling for series production systems during operation, including setup and shutdown activities. The flow shop system together with setup, shutdown times and energy consumption are considered. Production tasks enter the system with exponentially distributed interarrival times and are carried out according to the times assumed as predefined. Tasks arriving from one waiting queue are handled in the order set by the Multi Objective Immune Algorithm. Tasks are stored in a finite-capacity buffer if machines are busy, or setup activities are being performed. Whenever a production system is idle, machines are stopped according to shutdown times in order to save energy. A machine requires setup time before executing the first batch of jobs after the idle time. Scientists agree that turning off an idle machine is a common measure that is appropriate for all types of workshops, but usually requires more steps, such as setup and s... [more]

This study develops system-level models of ammonia-fuelled powertrains that reflect the characteristics of four oceangoing vessels to evaluate the efficacy of ammonia as an alternative fuel in the marine environment. Relying on thermodynamics, heat transfer, and chemical engineering, the models adequately capture the behaviour of internal combustion engines, gas turbines, fuel processing equipment, and exhaust aftertreatment components. The performance of each vessel is evaluated by comparing its maximum range and cargo capacity to a conventional vessel. Results indicate that per unit output power, ammonia-fuelled internal combustion engines are more efficient, require less catalytic material, and have lower auxiliary power requirements than ammonia gas turbines. Most merchant vessels are strong candidates for ammonia fuelling if the operators can overcome capacity losses between 4% and 9%, assuming that the updated vessels retain the same range as a conventional vessel. The study also... [more]

Forecasting renewable energy sources is of critical importance to several practical applications in the energy field. However, due to the inherent volatile nature of these energy sources, doing so remains challenging. Numerous time-series methods have been explored in literature, which consider only one specific type of renewables (e.g., solar or wind), and are suited to small-scale (micro-level) deployments. In this paper, the different types of renewable energy sources are reflected, which are distributed at a national level (macro-level). To generate accurate predictions, a methodology is proposed, which consists of two main phases. In the first phase, the most relevant variables having impact on the generation of the renewables are identified using correlation analysis. The second phase consists of (1) estimating model parameters, (2) optimising and reducing the number of generated models, and (3) selecting the best model for the method under study. To this end, the three most-rele... [more]

Battery energy storage systems (BESSs) are key components in efficiently managing the electric power supply and demand in microgrids. However, the BESSs have issues in their investment costs and operating lifetime, and thus, the optimal sizing of the BESSs is one of the crucial requirements in design and management of the microgrids. This paper presents a problem framework and its solution method that calculates the optimal size of the BESSs in a microgrid, considering their cooperative operations with the other components. The proposed framework is formulated as a bi-level optimization problem; however, based on the Karush−Kuhn−Tucker approach, it is regarded as a type of operation scheduling problem. As a result, the techniques developed for determining the operation schedule become applicable. In this paper, a combined algorithm of binary particle swarm optimization and quadratic programming is selected as the basis of the solution method. The validity of the authors’ proposal is ve... [more]

Utility-scale hybrid wind−solar PV power plants (which might include some storage as well) are an attractive option for the transition of conventional grids to incorporate high renewable energy (RE) shares. Along with lower generation costs, they offer increased dispatch capabilities and flexible operation. However, when assessing their potential, they present higher needs in terms of input data, as they are forced to consider both spatial and temporal variations to evaluate their techno-economic viability, as well as other common inputs such as economic, social or environmental data. The availability of the different data influences the type of analysis to be implemented. The microgrid approach of segmenting the information into layers will be adopted for the classification of data. Three different levels of analysis are sought: long-term energy scenarios, geo-spatial planning, and production cost estimation. The analysis of necessary data for each planning stage, and the available da... [more]

Bucket elevators are applied in many industries for bulk material handling. One of the main requirements for these devices is their high operational reliability. This applies in particular to power units that must operate continuously without failure. This article presents a comparative assessment of the drive units of two bucket elevators. The vibration intensity of their bearing units was used as the basis for the comparison. The evaluation was carried out using three independent methods based on the vibration velocity analysis: in the time domain, in the frequency domain and using the probabilistic approach.

Large-scale wind farms and wind farm clusters with many installed wind turbines are increasingly built around the world, and especially in offshore regions. The reliability and availability of these assets are critically important for cost-effective wind power generation. This requires effective solutions for online fault detection, diagnosis and fault accommodation to improve the overall reliability and availability of wind turbines and entire wind farms. To meet this requirement, this paper proposes a novel active fault-tolerant cooperative control (FTCC) scheme for large-scale wind farms and wind farm clusters (WFCs). The proposed scheme is based on a signal correction method at wind turbine level that is augmented with two innovative “control reallocation” mechanisms at wind farm and network operator levels. Applied to a WFC, this scheme detects, identifies and accommodates the effects of both mild and severe power-loss faults in wind turbines. Various simulation studies on an adva... [more]

Indoor heating systems currently used are highly dependent on fossil fuels; hence, it is urgent to develop a new heating system to achieve carbon zero-emission. A solar air heater is eco-friendly because it generates nearly zero greenhouse gases. In this study, a parametric study was conducted for optimizing solar air heater design applicable to indoor heating. Installing the internal structure in the solar heater changes the interior flow characteristic, resulting in the air temperature increased by about 14.2 K on average compared to the heater without the internal structure. An additional case study was carried out to optimize the ideal quantity of phase change materials (PCM) in terms of mass fraction and heat capacity for various operating conditions. An excessive amount of PCM (e.g., 66% of the storage space filled with PCM) deteriorates the performance of the air heater unless the entire PCM could be melted during the daytime. After heating, the air temperature was maintained th... [more]

The adoption of Virtual Reality (RV) technologies in prototype design and process revision has contributed to multiple industry areas. Nonetheless, the development of VR systems for engineering is a complex task, as it involves specialized teams handling low-level code development. Given these problems, the goal of this study is presenting a methodology for designing VR, through an Authoring System based on Computer-Aided Design (CAD). The presented methodology provides an easy integration of electric power substation floor plans and Virtual Reality software (VRS), as well as three-dimensional and symbol modeling conventions. Centralized software architecture was developed, composed of the CAD Editor, input manager and VRS. The methodology was evaluated through a case study applied to the conception (elaboration) of electric power substations (EPS) as part of a Research and Development (R&D) project for training and field assets supervision. The results demonstrated visual precision an... [more]

This paper puts forward a methodology for calculating the duration and energy efficiency of regimes for autoclave steaming of wooden prisms for veneer production at limited heat power of the steam generator, depending on the dimensions of the prism’s cross section, wood moisture content, and loading level of the autoclave. The methodology is based on the use of two personal mathematical models: the 2D non-linear model of the temperature distribution in non-frozen wooden prisms subjected to steaming and subsequent conditioning in an air medium, and the model of the non-stationary heat balance of autoclaves for steaming wood materials. Using the suggested methodology, the calculation and research into the duration and energy efficiency of regimes for heating of beech prisms have been carried out. The variables used were an initial temperature of 0 °C, cross-section dimensions 0.3 × 0.3 m, 0.4 × 0.4 m, and 0.5 × 0.5 m, moisture content of 0.4, 0.6, and 0.8 kg·kg−1, during their steaming i... [more]

Connected vehicles have emerged as the latest revolution in the automotive industry, utilizing the advent of the Internet of Things (IoT). However, most IoT-connected cars mechanisms currently depend on available network services and need continuous network connections to allow users to connect to their vehicles. Nevertheless, the connectivity availability shortcoming in remote or rural areas with no network coverage makes vehicle sharing or any IoT-connected device problematic and undesirable. Furthermore, IoT-connected cars are vulnerable to various passive and active attacks (e.g., replay attacks, MiTM attacks, impersonation attacks, and offline guessing attacks). Adversaries could all use these attacks to disrupt networks posing a threat to the entire automotive industry. Therefore, to overcome this issue, we propose a hybrid online and offline multi-factor authentication cross-domain authentication method for a connected car-sharing environment based on the user’s smartphone. The... [more]

Development of high-frequency-isolated DC-DC converters is underway for charging and discharging electric vehicle batteries. As a charger, a Single Active Bridge (SAB) converter, which is composed of a primary full-bridge converter, a high-frequency transformer, and a secondary full-bridge diode rectifier circuit, has been proposed as a unidirectional high frequency isolated DC-DC converter. In this paper, as a simple circuit configuration, a Secondary-Resonant Single-Active-Half-Bridge (SR-SAHB) converter, in which the primary and secondary circuits of the SAB converter are both half-bridge circuits, and a resonant capacitor connected in parallel to each secondary diode, is created. Due to the partial resonance on the secondary side, power transmission with unity transformer turn ratio and unity voltage conversion ratio can be realized, and a high total input power factor of the transformer can be achieved. As a result, the maximum voltage and current of the switching devices and the... [more]

Transportation agencies optimize signals to improve safety, mobility, and the environment. One commonly used objective function to optimize signals is the Performance Index (PI), a linear combination of delays and stops that can be balanced to minimize fuel consumption (FC). The critical component of the PI is the stop penalty “K”, which expresses an FC stop equivalency estimated in seconds of pure delay. This study applies vehicular trajectory and FC data collected in the field, for a large fleet of modern vehicles, to compute the K-factor. The tested vehicles were classified into seven homogenous groups by using the k-prototype algorithm. Furthermore, multigene genetic programming (MGGP) is utilized to develop prediction models for the K-factor. The proposed K-factor models are expressed as functions of various parameters that impact its value, including vehicle type, cruising speed, road gradient, driving behavior, idling FC, and the deceleration duration. A parametric analysis is c... [more]

Separating oil-water mixtures is critical in a variety of practical applications, including the treatment of industrial wastewater, oil spill cleanups, as well as the purification of petroleum products. Among various methodologies that have been utilized, membranes are the most attractive technology for separating oil-water emulsions. In recent years, selective wettability membranes have attracted particular attention for oil-water separations. The membrane surfaces with hydrophilic and in-air oleophobic wettability have demonstrated enhanced effectiveness for oil-water separations in comparison with underwater oleophobic membranes. However, developing a hydrophilic and in-air oleophobic surface for a membrane is not a trivial task. The coating delamination process is a critical challenge when applying these membranes for separations. Inspired by the above, in this study we utilize poly(ethylene glycol)diacrylate (PEGDA) and 1H,1H,2H,2H-heptadecafluorodecyl acrylate (F-acrylate) to fab... [more]

This study examines the relationship between urbanization, economic growth, industrial transformation, technological change, public services, demographical change, urban and natural environmental changes, and carbon emissions using a dataset of 182 prefecture-level cities in China between 2001 and 2010. Specifically, this paper differs from previous studies in two aspects. First, the extant literature has focused on how economic processes accompanying rapid urbanization affect carbon emissions in urban areas but gives little attention to the other dimensions of urbanization, including social and environmental changes, which may have important effects on carbon emissions. We assessed the effects of 17 key processes accompanying urbanization in a full range of economic, social, and environmental dimensions on carbon dioxide emissions in urban areas. The results showed that social processes accompanied with rapid urbanization had distinct effects on carbon emissions, compared to economic... [more]

In recent years electricity sectors worldwide have undergone major transformations, referred to as the “energy transition”. This has required energy planning to quickly adapt to provide useful inputs to the regulation activity so that a cost-effective electricity market emerges to facilitate the integration of renewables. This paper analyzes the role of system planning and regulations on two specific elements in the energy market design: the concept of firm capacity and the presence of distributed energy resources, both of which can be influenced by regulation. We assess the total cost of different regulatory mechanisms in the Brazilian and Mexican systems using optimization tools to determine optimal long-term expansion for a given regulatory framework. In particular, we quantitatively analyze the role of the current regulation in the total cost of these two electricity systems when compared to a reference “efficient” energy planning scenario that adopts standard cost-minimization pri... [more]

Passive thermal comfort has been widely used to test the thermal performance of a building. The science of active thermal comfort is important to be connected with the science of architecture. The currently developing active thermal comfort is adaptive thermal comfort. Vernacular houses are believed to be able to create thermal comfort for the inhabitants. The present study seeks to analyze the connection between the architectural elements of vernacular houses and adaptive thermal comfort. A mixed method was applied. A quantitative approach was used in the measurement of variables of climate, while a qualitative methodology was employed in an interview on thermal sensations. The connection between architectural elements and adaptive thermal comfort was analyzed by considering the correlation among architectural features, the analysis results of thermal comfort, and the Olgyay and psychrometric diagrams. At the beginning of the rainy season, residents of exposed stone houses had the hig... [more]

An analysis is performed with regards to technologically outdated heating plants operating in many areas where fossil fuels such as coal and gas are utilized, in order to consider the alternatives of their modernization. By application of a chart using a variety of alternatives, the economic feasibility of executing two types of modernization of heating plants are explored: a single-fuel gas−steam CHP plant and a coal-fired heating plant to a coal-fired CHP plant with a condensing turbine. This study demonstrates how the selection of modernization technology is affected, in terms of profitability, by the value and variability in time of the price relationships between energy carriers, rapidly growing charges related to CO2 emission allowances, and costs depending on other pollutant emissions that originate from the operation of electricity and heat sources powered by fossil fuels. In both technical cases of modernization, lower prices of energy carriers coupled with CO2 emissions allow... [more]

The use of concentrated solar irradiation for the improvement of electric generation improvement has been implemented on different scales, mainly in photovoltaic systems. High-concentration Fresnel lenses are widely chosen for this approach in large installations, while low-concentration systems are rather applied in medium-low scales. For the latter, the improvement on electric performance was revealed, even when no solar tracking was implemented. The presented work aims to analyse a low-concentration photovoltaic installation by a numerical approach. First, the reflective surfaces were designed geometrically considering the optimal slope determined for each month. Subsequently, different simulation techniques were used separately for prediction of solar irradiation and energy production. Three criteria were selected to analyze power generation: the highest increase in total annual solar irradiance on panels with reflective surfaces, the highest total annual solar irradiance collected... [more]

The state estimation of distribution networks has long been considered a challenging task for the reduced availability of real-time measures with respect to the transmission network case. This issue is expected to be improved by the deployment of modern smart meters that can be polled at relatively short time intervals. On the other hand, the management of the information coming from many heterogeneous meters still poses major issues. If low-voltage distribution systems are of interest, a three-phase formulation should be employed for the state estimation due to the typical load imbalance. Moreover, smart meter data may not be perfectly synchronized. This paper presents the implementation of a three-phase state estimation algorithm of a real portion of a low-voltage distribution network with distributed generation equipped with smart meters. The paper compares the typical state estimation algorithm that implements the weighted least squares method with an algorithm based on an iterated... [more]

The main purpose of this study is to optimize engine performance and emission characteristics of off-road engines with retarded spark timing compared to MBT by repurposing the existing passenger engine. This study uses a one-dimensional (1D)-simulation to develop a non-road gasoline MPI turbo engine. The SI turbulent flame model of the GT-suite, an operational performance predictable program, presents turbocharger matching and optimal operation design points. To optimize the engine performance, the SI turbulent model uses three operation parameters: spark timing, intake valve overlap, and boost pressure. Spark timing determines the initial state of combustion and thermal efficiency, and is the main variable of the engine. The maximum brake torque (MBT) point can be identified for spark timing, and abnormal combustion phenomena, such as knocking, can be identified. Spark timing is related to engine performance, and emissions of exhaust pollutants are predictable. If the spark timing is... [more]