Primary Constraint Research Articles

Geometric optimisation analysis of Steel–Concrete hybrid wind turbine towers

Steel–concrete hybrid towers have been proposed for onshore tall wind turbine tower installations. Their bottom sections are built with concrete and top sections with steel. The primary advantages of such hybrid towers include construction using low-cost durable material and avoidance of transport barriers associated with all-steel towers. In this study, a set of design constraints governing the geometry of hybrid towers was proposed to determine the optimal combination of concrete and steel sections. The primary constraint in tower design involves avoiding resonance because a resonant response can significantly damage the tower and trigger turbine fault conditions. A sensitivity analysis was conducted to explore the correlation between the natural frequency and geometry of a tower. The results demonstrated that an increase in the proportion of concrete can lead to a pronounced effect on the first modal frequency of taller towers. Additionally, geometric optimisation was performed on a 160 m tall tower. This resulted in a 12.7% reduction in the total cost compared with that of the initial design.

A Critical Perspective on Positive Energy Districts in Climatically Favoured Regions: An Open-Source Modelling Approach Disclosing Implications and Possibilities

Urban areas have been responsible for the majority of the European Union (EU)-wide primary energy demand and CO2 emissions. To address this issue, the European Union introduced the concept of Positive Energy Districts (PEDs). PEDs are required to have an annual positive primary energy balance. However, if directly addressed in the literature, this energy balance only includes annually fixed primary energy factors and often neglects grid impacts. To bridge this gap, this work proposes a mathematical optimisation approach for PEDs, working towards an open-source model. The model’s main novelty is an hourly primary energy balance constraint. The performed case study on the island La Palma for both an urban and a rural neighbourhood show that the PED concept has a higher net present value (NPV) than solely buying electricity from the grid in all feasible cases. Depending on the space available for PV installations, the NPV increases between 29 and 31% and 25–27% for the rural and urban PED scenarios, respectively. However, in the scenarios with reduced grid impact, the NPV decreases due to the expensive battery installations. Comparing the significantly fossil-based electricity grid mix of La Palma with the renewable-based one of El Hierro shows that the primary energy-based optimisation has more room for flexibility in the high renewable mix. While the dynamic primary energy balance constraint appears promising for operational optimisation, the allocation of correct primary energy factors is crucial.

Constraints to Pearl Millet (Pennisetum glaucum) Production and Farmers’ Approaches to Striga hermonthica Management in Burkina Faso

Pearl millet (Pennisetum glaucum) is a staple food crop in Burkina Faso that is widely grown in the Sahelian and Sudano-Sahelian zones, characterised by poor soil conditions and erratic rainfall, and high temperatures. The objective of this study was to document farmers’ perceptions of the prevailing constraints affecting pearl millet production and related approaches to manage the parasitic weeds S. hermonthica. The study was conducted in the Sahel, Sudano-Sahelian zones in the North, North Central, West Central, Central Plateau, and South Central of Burkina Faso. Data were collected through a structured questionnaire and focus group discussions involving 492 participant farmers. Recurrent drought, S. hermonthica infestation, shortage of labour, lack of fertilisers, lack of cash, and the use of low-yielding varieties were the main challenges hindering pearl millet production in the study areas. The majority of the respondents (40%) ranked S. hermonthica infestation as the primary constraint affecting pearl millet production. Respondent farmers reported yield losses of up to 80% due to S. hermonthica infestation. 61.4% of the respondents in the study areas had achieved a mean pearl millet yields of <1 t/ha. Poor access and the high cost of introduced seed, and a lack of farmers preferred traits in the existing introduced pearl millet varieties were the main reasons for their low adoption, as reported by 32% of respondents. S. hermonthica management options in pearl millet production fields included moisture conservation using terraces, manual hoeing, hand weeding, use of microplots locally referred to as ‘zaï’, crop rotation and mulching. These management techniques were ineffective because they do not suppress the below ground S. hermonthica seed, and they are difficult to implement. Integrated management practices employing breeding for S. hermonthica resistant varieties with the aforementioned control measures could offer a sustainable solution for S. hermonthica management and improved pearl millet productivity in Burkina Faso.

CLeaR: An adaptive continual learning framework for regression tasks

Catastrophic forgetting means that a trained neural network model gradually forgets the previously learned tasks when being retrained on new tasks. Overcoming the forgetting problem is a major problem in machine learning. Numerous continual learning algorithms are very successful in incremental learning of classification tasks, where new samples with their labels appear frequently. However, there is currently no research that addresses the catastrophic forgetting problem in regression tasks as far as we know. This problem has emerged as one of the primary constraints in some applications, such as renewable energy forecasts. This article clarifies problem-related definitions and proposes a new methodological framework that can forecast targets and update itself by means of continual learning. The framework consists of forecasting neural networks and buffers, which store newly collected data from a non-stationary data stream in an application. The changed probability distribution of the data stream, which the framework has identified, will be learned sequentially. The framework is called CLeaR (Continual Learning for Regression Tasks), where components can be flexibly customized for a specific application scenario. We design two sets of experiments to evaluate the CLeaR framework concerning fitting error (training), prediction error (test), and forgetting ratio. The first one is based on an artificial time series to explore how hyperparameters affect the CLeaR framework. The second one is designed with data collected from European wind farms to evaluate the CLeaR framework’s performance in a real-world application. The experimental results demonstrate that the CLeaR framework can continually acquire knowledge in the data stream and improve the prediction accuracy. The article concludes with further research issues arising from requirements to extend the framework.

Integrated assessments call for establishing a sustainable meta-population of Amur tigers in northeast Asia

With most large carnivore populations and habitats suffering massive declines across the world, efforts to restore their populations in the wild are of high conservation priority. China attaches great importance to protecting Amur tigers and has made considerable progress towards this goal, but most efforts have been focused on the single Laoyeling landscape. Here we assess all four major forested landscapes (including Laoyeling, Zhangguangcailing, Wandashan and Lesser Khinghan Mountains) that may be suitable for tigers in northeast China. Between 2013 and 2018, in total 55 wild Amur tigers were recorded through camera trap surveys and 30 individuals were identified through genetic analyses. The finite rate of increase of the population in the Laoyeling landscape, the only landscape with a breeding population, fluctuated greatly, but averaged 1.51. Total habitat used by Amur tigers during this period amounted to 47,813 km2. We estimated that based on density and home range sizes in nearby Russia, these landscapes could support 310 tigers, including 119 resident breeding females. However, prey density, especially of preferred prey, was extremely low, and likely a primary constraint to population recovery in landscapes other than Laoyeling, especially the Wandashan and Lesser Khingan Mountains landscapes. To achieve the goal of a large meta-population of Amur tigers across northeast Asia, in addition to prey restoration, we recommend extensive landuse planning, reducing anthropogenic impacts, improving ecology connectivity, and extensive international cooperation, as well as a feasibility assessment for introducing orphaned cubs as a means of speeding recovery in landscapes without breeding females.

Structural Equation Modelling (SEM) Approach On Inappropriate Construction Equipment Delay Factors

The advancement of construction equipment is a trend in the construction industry, with numerous benefits. However, using inappropriate construction equipment causes delays in construction projects, affecting the firm's reputation. A number of research studies on overall delay have been conducted globally. Even so, there is a lack of research on construction delays caused by inappropriate construction equipment. The aim of this paper is to investigate the inappropriate construction equipment delay factors and their effects on the firm's reputation. Based on the issues identified in the focus group interviews and the literature survey, a questionnaire survey was conducted to assess the impact of these factors on the progress of Indian construction projects. The primary constraint was that all 300 responses were collected in person from construction professionals to avoid lethargic responses that could skew the results. Pearson correlation coefficients were used to determine the positive strength of each factor's relationship. A t-test was used to see if there was a significant difference between the respondents' firm categories. Structural Equation Modeling (SEM) was used to validate the effective relationship between the causes of delays due to inappropriate construction equipment and its impact on company's reputation. All of the factors examined by the SEM analysis evidenced that the inappropriate construction equipment factors are correlated among themselves and combined to impact the reputation of the company. Recommendations are made to overcome the inappropriate equipment delay factors. Doi: 10.28991/cej-2021-03091717 Full Text: PDF

Review of the Hamiltonian analysis in teleparallel gravity

We review different approaches to the Hamiltonian analysis of teleparallel theories of gravity. In particular, the Hamiltonian analysis for [Formula: see text] theories led to disputed results in the literature. The aim of this review is to relate the different notations and assumptions in the different approaches in a comprehensive way, so that they can be compared more easily. To do this we present the primary constraints of the [Formula: see text] gravity class of theories for the first time. The particular cases studied in the literature, [Formula: see text] gravity and new general relativity, are contained in this parent theory. We compare their Hamiltonian analyses done by different authors in the literature among each other by relating them to our analysis of [Formula: see text] in detail.

List Decoding of Arıkan's PAC Codes.

Polar coding gives rise to the first explicit family of codes that provably achieve capacity with efficient encoding and decoding for a wide range of channels. However, its performance at short blocklengths under standard successive cancellation decoding is far from optimal. A well-known way to improve the performance of polar codes at short blocklengths is CRC precoding followed by successive-cancellation list decoding. This approach, along with various refinements thereof, has largely remained the state of the art in polar coding since it was introduced in 2011. Recently, Arıkan presented a new polar coding scheme, which he called polarization-adjusted convolutional (PAC) codes. At short blocklengths, such codes offer a dramatic improvement in performance as compared to CRC-aided list decoding of conventional polar codes. PAC codes are based primarily upon the following main ideas: replacing CRC codes with convolutional precoding (under appropriate rate profiling) and replacing list decoding by sequential decoding. One of our primary goals in this paper is to answer the following question: is sequential decoding essential for the superior performance of PAC codes? We show that similar performance can be achieved using list decoding when the list size L is moderately large (say, ). List decoding has distinct advantages over sequential decoding in certain scenarios, such as low-SNR regimes or situations where the worst-case complexity/latency is the primary constraint. Another objective is to provide some insights into the remarkable performance of PAC codes. We first observe that both sequential decoding and list decoding of PAC codes closely match ML decoding thereof. We then estimate the number of low weight codewords in PAC codes, and use these estimates to approximate the union bound on their performance. These results indicate that PAC codes are superior to both polar codes and Reed–Muller codes. We also consider random time-varying convolutional precoding for PAC codes, and observe that this scheme achieves the same superior performance with constraint length as low as .

Constraints Encountered by Rural Youth for Establishment of Agri-Enterprises and Elicit Suggestions to Overcome Them

India is with a high level of youth unemployment. Markets have insufficient jobs to absorb young job seekers. The purpose of the study was to identify constraints and suggestions that are faced by the rural youth who are engaged in agri-enterprises. A sample of 240 youth involved in agripreneurshipwasgiven questionnaires. The findings of the study indicated that the youth faced many challenges while establishing their agri-enterprises.The primary constraint faced by rural youth were economic constraints followed by technical constraints, psychological constraints, extension-related constraints, social constraints,and other constraints. The constraints perceived and the suggestions given by the rural youth for the establishment of agri-enterprises to overcome their constraints were observed and depicted.

Effective Crop Management and Modern Breeding Strategies to Ensure Higher Crop Productivity under Direct Seeded Rice Cultivation System: A Review

Paddy production through conventional puddled system of rice cultivation (PTR) is becoming more and more unsustainable—economically and environmentally—as this method is highly resource intensive and these resources are increasingly becoming scarce, and consequently, expensive. The ongoing large-scale shift from puddled system of rice cultivation PTR to direct seeded rice (DSR) necessitates a convergence of breeding, agronomic and other approaches for its sustenance and harnessing natural resources and environmental benefits. Current DSR technology is largely based on agronomic interventions applied to the selected varieties of PTR. In DSR, poor crop establishment due to low germination, lack of DSR-adapted varieties, high weed-nematode incidences and micronutrient deficiency are primary constraints. The approach of this review paper is to discuss the existing evidences related to the DSR technologies. The review highlights a large number of conventionally/molecularly characterized strains amenable to rapid transfer and consolidation along with agronomic refinements, mechanization and water-nutrient-weed management strategies to develop a complete, ready to use DSR package. The review provides information on the traits, donors, genes/QTL needed for DSR and the available DSR-adapted breeding lines. Furthermore, the information is supplemented with a discussion on constrains and needed policies in scaling up the DSR adoption.

Exploring the Relationship between Information-Seeking Behavior and Adoption of Biofertilizers among Onion Farmers

Recently, there has been increasing concern about reducing and replacing chemical fertilizers with biofertilizers to enhance soil fertility and maintain agroecosystems and sustainable agricultural production. Given that knowledge of biofertilizers is information-intensive, the lack of information-seeking behavior (ISB) might be the primary constraint for farmers adopting biofertilizers. This study aimed to analyze how ISB influences farmers’ adoption of biofertilizers, using a sample of 228 onion farmers in Al-Ahsa Governorate, Saudi Arabia. The results indicate that most farmers had a moderate level of ISB. The most frequently accessed sources were mobile applications, extension institutions, and progressive farmers. The results of cluster analysis show that farmers’ ISB differed significantly according to their main occupation. Among the onion farmers, 35%had adopted biofertilizers. The findings also reveal that farm size, attitude toward biofertilizers, the credibility of information sources, and the usefulness of the information positively and significantly influence farmers’ adoption of biofertilizers. It was concluded that understanding the relationship between adoption and ISB could assist policymakers in focusing on knowledge diffusion when designing extension programs and advisory services to facilitate better usage of biofertilizers.

Climatic constraints to yield and yield components of temperate japonica rice

AbstractAlthough temperate japonica rice (Oryza sativa L.) production is limited by both low‐ and high‐temperature stresses, the primary constraint was reported to be cold stress in the past. However, the magnitudes of low‐ and high‐temperature stresses may have been altered by global warming. In this study, the major climatic constraints to the yield and yield components of temperate japonica rice grown in field conditions under the current climates were assessed using the random forests method with 14‐yr field trial data (n = 499). Low temperatures had negligible impacts on rice yield under the current climates (2005–2018) in South Korea. Meanwhile, high‐temperature stress was most significant during the ripening stage, followed by the reproductive stage. Yield losses by high temperatures were primarily associated with reduced filled‐grain percentage, followed by reduced 1,000‐grain weight. During the vegetative stage, higher temperature (or higher growing degree days, GDD) decreased the number of panicles per m2 and increased the number of spikelets per panicle, resulting in negligible changes in the number of spikelets per m2 and yield. The effect of solar radiation was most significant during the ripening stage. More solar radiation during the ripening stage enhanced rice yield by increasing filled‐grain percentage and 1,000‐grain weight. This study highlights that the primary constraints to temperate japonica rice grown under the current climates are high‐temperature stresses during the ripening and reproductive stages rather than low‐temperature stresses. Thus, there is an urgent need to explore options for improving the adaptation of temperate japonica rice to anticipated global warming.

Overexpression of EcDREB2A transcription factor from finger millet in tobacco enhances tolerance to heat stress through ROS scavenging

An extreme temperature regime beyond desired level imposes significant stress in crop plants. The low and high temperature stresses are one of the primary constraints for plant development and yield. Finger millet, being a climate resilient crop, is a potential source of novel stress tolerant genes. In this study, functional characterization of finger millet DREB2A gene in different abiotic stress conditions was done. This novel EcDREB2A transcription factor isolated from finger millet is a truncated version of DREB2A gene compared to previously reported DREB genes from other plant species. The overexpression of EcDREB2A in transgenic tobacco exhibits improved tolerance against heat stress 42 °C for up to 7 days, by altering physiology and biochemical means. However, same transgenic lines were unable to provide tolerance to 200 mM NaCl and 200 mM Mannitol stress. Under heat stress conditions, increased seed germination with improved lateral roots, fresh and dry weight relative to wild type (WT) was observed. The EcDREB2A transgenics exposed to heat stress showed improved rate of stomatal conductance, chlorophyll and carotenoids contents, and other photosynthesis parameters compared to WT plants. EcDREB2A overexpression also resulted in increased antioxidant enzyme activity (SOD, CAT, GR, POD and, APX) with decreased electrolyte leakage (EL), H2O2, and malondialdehyde (MDA) content than WT plants under heat stress. Quantitative real time expression analysis demonstrated that all eight downstream genes were significantly upregulated in transgenic plants only after heat stress. Our data provide a clear demonstration of the positive impact of overexpression of EcDREB2A providing heat stress tolerance to plants.

Consumer awareness, practices and purchasing behavior towards green consumerism in Kenya

Sustainable consumption and production are related to maximizing natural resource use while minimizing waste generation to reduce the environment's negative impacts. There has been limited research on consumer approaches to Kenya's environmental concerns, and their consumption behaviours remain unknown. This study sought to assess the Kenyan consumers' knowledge of green products, their sustainable practices (SCP), and eco-labels influence on their purchasing decisions. A semi-structured questionnaire was administered to 205 participants randomly selected in five constituencies within Nairobi County. The consumer's educational level significantly (p<0.01) correlated with the knowledge of sustainable consumption and production (39%) as compared to 61% who are not aware of SCP practices. However, SCP knowledge was not significantly different (p=0.76) among the male and female respondents. The prices (86.3%) and product quality (79.5%) were the most considered during purchase than only 40% of the consumers who preferred environmentally friendly products during purchase. Even though only 27% agreed that eco-labelling plays a key role when purchasing products, most (70%) of the respondents would buy green products if green credentials were emphasized. The respondents' trust levels on eco-labels were not significantly different among male and female respondents (c2 = 5.89, p=0.47) and regardless of the educational levels (c2 = 5.51, p=0.99), However, the high costs (69.8%), lack of adequate information (44.4%), and unavailability (39.5%) were the primary constraints to buying green products. While environmental activists were found to be the most important (66.1%) sources of information, increased awareness (98%), environmental education (90.7%), and provision of monetary incentives (78%) would help promote sustainable consumption and production. In conclusion, there is a need for creating more awareness on the consumption and production of green horticultural food products to sensitize the public on sustainable environmental practices among Kenyan consumers to promote green consumerism.

Standardization of electric vehicle battery pack geometry form factors for passenger car segments in India

The Electric Vehicles (EV) adaptability is at the early stage in India due to many performances and commercial constraints among the potential customers. Battery Electric Vehicles (BEV) are slowly picking up in the Indian market and likely to grow due to stringent Government regulations and Green Mobility initiatives. The primary constraint in EV purchase is the driving range offered by Original Equipment Manufacturers (OEM) and EV range anxiety. This paper discusses the current battery pack integration among Indian Original Equipment Manufacturers (OEMs), design challenges, and the need for Standardised Battery Pack envelope (SBP). This study analyses the India OEMs vehicle data and, using a statistical and engineering assessment model, recommends the critical standard dimensions, type, size for the Standardised Battery Pack (SBP). This is possible by means of Electric Vehicle (EV) skateboard platform architecture, and platform sharing proliferate among EV manufacturers and start-ups. The model verifies the results by analytical and Simulation techniques. The results show the proposed model with SBP gives higher flexibility, improved driving range ,convenient battery swapping operation, improved operation time, and helps in second-life applications. This study's limitation is that due to the rapid advancement in battery technology, a specific battery chemistry is under consideration throughout the study.

Day-ahead hourly photovoltaic power forecasting using attention-based CNN-LSTM neural network embedded with multiple relevant and target variables prediction pattern

Accurate forecasting of photovoltaic power plays a pivotal role in the integration, operation, and scheduling of smart grid systems. Notably, volatility and intermittence of solar energy are the primary constraints influencing the accuracy of photovoltaic power prediction. This work proposes, an attention-based long-term and short-term temporal neural network prediction model (ALSM) assembled using the convolutional neural network (CNN), long short-term memory neural network (LSTM), and attention mechanism under the multiple relevant and target variables prediction pattern (MRTPP). This is geared towards capturing the short-term and long-term temporal modes and achieving the day-ahead hourly photovoltaic power forecasting. The proposed method is verified by the historical data of the photovoltaic system downloaded from the DKASC website. Consequently, the results indicate that the forecasting accuracy using the MRTPP pattern is better than those common input-output prediction patterns. Moreover, the proposed ALSM model under the MRTPP pattern demonstrates more superiority compared to a few PV power forecasting methods including the statistical methods as well as artificial intelligence methods. Subsequently, different important parameters affecting the accuracy of forecasting range of the model are analyzed, and suggestions on memory lengths corresponding to the divergent prediction range are provided.

A single phase five-level inverter with single and multiple switch fault tolerance capabilities

The reliability of multilevel inverters (MLIs) is of great importance, when they are employed for applications such as aircrafts, electric vehicles, standalone, and grid connected photovoltaic (PV) system. To achieve required output voltage during post-fault scenarios, several fault tolerant topologies of multilevel inverter have been proposed. However, the primary constraints which add on a limitation to their implementation are increased device count and inability to tolerate single and multiple switch faults with the conduction of lesser or equal switches as in pre-fault case. The inability to tolerate various types of faults, such as open circuit or short circuit, cause severe impact on the system and further increase the cost. In this regard, a fault tolerant (FT) multilevel inverter topology which tolerates aforementioned faults is proposed. The proposed topology is able to withstand both single switch and multiple switch faults with equal or lesser blocking voltage. The proposed topology employs only unidirectional switches, thus increasing the reliability and reducing the cost of inverter. The proposed work is validated experimentally.

Proposed Model of Sustainable Resource Management for Smart Grid Utilization

Automation and modernization of the grid with the availability of micro-grids including non-conventional sources of energy are the main constituent of smart grid technology. Most energy demand is fulfilled by fossil fuel-based power plants. Inadequacy of fuel resources, higher operating costs, and ever-increasing carbon emissions are the primary constraints of fossil fuels-operated power plants. Sustainable energy resource utilization in meeting energy demand is thought to be a preferred solution for reducing carbon emissions and is also a sustainable economic solution. This research effort discusses an accurate mathematical modeling and simulation implementation of a sustainable energy resource model powered by solar, grid, and proton exchange membrane fuel cell (PEMFC) stack and focuses on the energy management of the model. In the proposed model, despite energy resources being sustainable, consumer side sustainability is achieved by using electrical charging vehicles (ECVs) to be integrated with sustainable resources. The proposed energy resource management (ERM) strategy is evaluated by simulating different operating conditions with and without distributed energy resources exhibiting the effectiveness of the proposed model. PEMFC is incorporated in the model to control fluctuations that have been synchronized with other energy resources for the distribution feeder line. In this proposed model, PEMFC is synchronized with grid and solar energy sources for both DC and AC load with ERM of all sources, making the system effective and reliable for consumer-based load and ECVs utilization.

Examination of the Mechanical, Corrosion, and Tribological Behavior of Friction Stir Welded Aluminum Alloy AA8011

Aluminum alloy AA8011 is emerging as a promising material for modern engineering applications in which improved tensile strength, hardness, corrosion-resistance, and wear-resistance of materials are required. Typically, AA8011 alloys are utilized in air-conditioning ducts and heat exchanger fins in ships, leisure boats, luxury vessels, workboats, fishing vessels, and patrol boats. However, the conventional welding of AA8011 is a challenging procedure. In this context, this paper focuses on the development of an effective solid-state welding methodology for AA8011 alloy welding. The AA8011 alloy was friction stir welded by varying the tool rotation speed, traverse speed, and shoulder diameter. The microhardness, tensile strength, joint efficiency, elongation, corrosion rate, and wear rate of the friction stir welded specimens were compared with the base material. Fractography analysis was conducted after the tensile test and surface morphology analysis after corrosion and wear tests, using scanning electron microscopy. The compositional elements in the corroded and worn section of the specimens were analyzed using energy-dispersive X-ray spectroscopy. Based on the joint efficiency as a primary constraint, the optimum process parameters for friction stir welding of aluminum alloy AA8011 have been established as follows: tool rotation speed of 1200 rpm, tool traverse speed of 45 mm/min, and tool shoulder diameter of 21 mm.

A seasonally dynamic model of light at the stream surface

AbstractLight is a primary constraint on primary production and drives many ecological processes in stream ecosystems, yet light regimes have received considerably less attention than other factors...