Optimal Loading Factor Research Articles

Optimal Load Factors for Seismic Design of Buildings

This paper reviews the load combinations for the design of buildings established in the Federal District Building Regulations (RCDF-2004) and its Complementary Technical Standards (NTC-2004). New load factors are proposed to be specified in the next version of the RCDF. The combination of gravity load (dead load plus live load) and the combination of earthquake load (dead load, live load and earthquake load) are revised. A methodology is proposed to establish optimal load factors and combinations that guarantee the minimum expected total cost during the lifetime of the structure and that the probability of failure is at least equal to that implied in the RCDF-2004. Artificial Neural Networks are used to estimate structural reliability.

Optimization of cabin seating arrangement strategies based on the Wells-Riley risk theory.

Civil aviation transport is an important source of global respiratory disease spread due to the closely-spaced environment. In order to reduce the probability of infection of passengers, an improved Wells-Riley model for cabin passenger risk assessment have been given in this work, the cabin ventilation and passenger nose and mouth orientation were considered. The model's effectiveness has been verified with published data. Finally, how the load factor and use of an empty seat scheme are associated with the number of infected people was assessed. The results demonstrated that the number of infected people positively correlates with the passenger load factor, and the most suitable load factor can be determined by controlling the final number of infected people with the condition of the epidemic situation in the departure city. Additionally, infection risk was found to be lower among passengers in window seats than in those in aisle seats and middle seats, and keeping empty seats in the middle or aisle could reduce the cabin average probability of infection by up to 37.47%. Using the model developed here, airlines can determine the optimal load factor threshold and seating arrangement strategy to improve economic benefits and reduce the probability of passenger infection.

Bowley Insurance with Expected Utility Maximization of the Policyholders

This article studies the Bowley solution for a sequential game within the expected utility framework. We assume that the policyholders are expected utility maximizers and there exists a representative policyholder who faces a fixed loss with given probability and no loss otherwise. This policyholder selects the optimal indemnity function in response to the pricing kernel set by the insurer. Knowing the policyholder’s choice of indemnity function, the insurer adjusts the pricing kernel to maximize its expected net profit. This pricing kernel is of our central interest in this article, and in our setting the pricing kernel can be evaluated via the safety loading factor in an expected value premium principle. For a wide class of utility functions, we show that the optimal safety loading factor increases with respect to both the policyholder’s risk aversion level and the probability of zero loss. We also show that the insurance contract corresponding to the Bowley solution is Pareto dominated in the sense that both parties’ interests can be further improved, which shows the inefficiency of the Bowley solution. Some numerical examples are presented to illustrate the main results, and it is shown that both the policyholder and insurer can strictly benefit from the Bowley solution.

A Cognitive Beamforming Method via Range-Doppler Map Features for Skywave Radar

For skywave over-the-horizon radar, beamforming techniques are often used to suppress airspace radio frequency interference because the high-frequency band is shared by many devices. To address the problems that the traditional beamforming method is not capable of recognizing the electromagnetic environment and that its performance is greatly affected by the accuracy of signal feature estimation, a cognitive beamforming method using range-Doppler (RD) map features for skywave radar is proposed. First, the RD map is weighted by a local attention model, and then, texture features are extracted as the inputs to a support vector machine. Finally, the support vector machine is used to predict the optimal diagonal loading factor. Simulation results show that the output signal-to-interference-plus-noise ratio is improved compared with previous methods. The proposed method is suitable for many kinds of common unsatisfactory scenarios, making it beneficial for engineering implementation.

A capacity adaption optimization model for supernormal operation of urban rail transit networks

In response to urban rail transit capacity shortage, a capacity adaption optimization model for the new mixed train operation mode is proposed in the supernormal operation of urban rail transit networks. First, the characteristics of express-local train and long-short route slow train are analyzed to obtain the main influencing factors of capacity adaption. Moreover, various train types are simultaneously classified and recombined in the adaption train operation mode to maximize transportation capacity for passengers. A nonlinear mixed-integer programming model is established to maximize the total number of trains, improving train load rate and reducing the total passenger travel time. In addition, the actual case of Beijing Metro Line 1 is solved to demonstrate the feasibility and effectiveness of the proposed model. The optimal passenger travel time-saving rates of the morning and evening peak hours are 12.1% and 11.5%, respectively. The optimal utilization rates of capacity in the morning and evening peak hours are 79.5% and 84.5%, respectively. Meanwhile, the optimal load factor within the range of 0.7–0.9 would benefit the utilization of train resources and the passengers’ service level. The optimized results show that the proposed capacity adaption optimization model benefits for high service level and practical significance and rationality for operators.

ECONOMIC DAMAGE ASSESSMENT METHODOLOGY IN CASE OF TRANSFORMER LOAD RATIO DEVIATION

The aim of the study is to develop a methodology for assessing economic damage when the transformer load factor deviates. In the process of research, a method was used to determine the optimal load of a power transformer. A method for assessing economic damage in case of a deviation of its load factor has been developed. The optimal load factor of a power transformer has been determined according to the criterion of the minimum cost of money for the transformation of electrical energy. The load level of power transformers can be assessed by two criteria: by the maximum integral value of the effi ciency and by the minimum loss of money during the transformation of electricity. According to the proposed methodology, the assessment of damage is carried out when the load factor of the transformer deviates from the optimal values, for which the relative losses of electrical energy are calculated. The results obtained when evaluating energy and fi nancial and economic effi ciency show that when the load factor is overestimated relative to the optimal values, it is much more preferable to overestimate than underestimate. The reliability of the results is confi rmed by the satisfactory agreement of the calculated results with the experimental data obtained at the operating power plant.

Optimal reinsurance with model uncertainty and Stackelberg game

In this paper, we obtain an optimal reinsurance contract explicitly in the form of excess-of-loss with a limit when the risk measure is Range-Value-at-Risk. Then we study optimal reinsurance with model uncertainty, where the uncertainty set contains a greatest element in the sense of stochastic order. Furthermore, we study the Stackelberg game in reinsurance with model uncertainty. In order to illustrate how our findings can be applied in practice to determine the optimal reinsurance contract, we perform an empirical study using the Wisconsin Local Government Property Insurance Fund dataset. Tweedie distributions are fit to the building and contents loss amounts from the property fund, and used to determine the optimal loading factor, and reinsurance contract corresponding to the loading factor. From the analysis, we discover that some policies have more recoveries from the optimal reinsurance contract than the premium paid, while others have smaller recoveries than the premium.

Study of power transformer loading in rural power supply systems

The purpose of this study is to study the effect of loading power transformers (PT) in their continuous use on their energy efficiency on a real-life example of existing rural electric networks. It is noted that the vast majority of PT in rural areas have a very low load factor, which leads to an increase in specific losses of electric energy when this is transmitted to various consumers. It is planned to optimize the existing synchronized power supply systems in rural areas by creating new power supply projects in such a way as to integrate existing power sources and ensure the most efficient loading of power transformers for the subsequent transfer of these systems to isolated ones that receive power from distributed generation facilities. As an example, we use data from an electric grid company on loading power transformers in one of the districts of the Irkutsk region. Issues related to the determination of electric energy losses in rural PT at different numerical values of their load factors are considered. A computing device was developed using modern programming tools in the MATLAB system, which has been used to calculate and plot the dependence of power losses in transformers of various capacities on the actual and recommended load factors, as well as the dependence of specific losses during the transit of 1 kVA of power through a power transformer at the actual, recommended and optimal load factors. The analysis of specific losses of electric energy at the actual, recommended and optimal load factors of PT is made. Based on the analysis, the intervals of optimal load factors for different rated power of PT of rural distribution electric networks are proposed. It is noted that to increase the energy efficiency of PT, it is necessary to reduce idling losses by increasing the load of these transformers, which can be achieved by reducing the number of transformers while changing the configuration of 0.38 kV distribution networks.

Case study for design optimization using the digital twin approach

To ensure the mechanical load capability of new products, diverse strength analysis methods have to be used while the product design process (e.g. FEA). The main objective of these methods is the predictive analysis and determination of the operational load of the product. Based on this analysis, the structure and the topology of the product can be set adequately in terms of an optimal material utilization and load factor. Nowadays, the mechanical structure analysis can only be done based on estimated loading data, which are determined using approximative theoretical calculation methods. Furthermore, this approach does not consider the actual use and load of the product in the field. As a consequence, inaccurate determination of the material stress and product dimensioning can be accrued in most instances. To compensate this incertitude, design engineers set a high safety factor while designing new products, which lead to over-dimensioning of the products and to wasteful use of material and resources. Thanks to powerful sensors, data transmission and data processing technologies, it becomes nowadays easy to collect operating data of technical systems and process and to present and process them using a digital model in real time. This approach is known as digital twin. Using the digital twin concept an integrated and a comprehensive data model as image of real systems and processes with continuously update can be created. This approach opens new prospects within the design process of technical systems in terms of efficiency and sustainability. This paper will present and discuss a case study for the application of the digital twin approach within the product design. The aim of the case study is the investigation of the digital twin concept to obtain the material stress and load from the product operation accurately and to use them for load-oriented and efficient product design.

Case Study for an Operation-based Topology Optimization Using the Digital Twin Approach

In order to ensure the mechanical load capability of new products, diverse strength and load analysis methods have to be used while the product design process (e.g. FEA). The main objective of these methods is the predictive analysis of the operational load of the product. Based on this analysis, the structure and the topology of the product can be set adequately in terms of an optimal material utilization and load factor. Nowadays, the mechanical structure analysis can only be done based on estimated loading data, which are determined using approximative theoretical calculation methods. Furthermore, this approach does not consider the actual use and load of the product in the field. As a consequence, inaccurate determination of the material stress and product dimensioning can be accrued in most instances. In order to compensate this incertitude, design engineers set a high safety factor while designing new products, which lead to over-dimensioning of the products and to wasteful use of material and resources. Thanks to powerful sensors, data transmission and data processing technologies, it becomes nowadays easy to collect operating data of technical systems and process and to present and process it using a digital model in real time. This approach is known as digital twin. Using the digital twin concept an integrated and a comprehensive data model as image of real systems and processes with continuously update can be created. This approach opens new prospects within the design process of technical systems in terms of efficiency and sustainability. This paper presents and discusses a case study for the implementation of the digital twin approach in the product design of an arbor press. The aim of this case study is the investigation of the digital twin concept to obtain the material stress and load from the product operation accurately and to use them for material-saving product design.

Optimal load factors for earthquake-resistant design of buildings located at different types of soils

This paper addresses the influence of the local soil type (firm or soft) on the reliability-based optimal load combination factors for seismic design of buildings. The approach aims to minimize the total expected life-cycle cost (LCC) of a structure. As a constraint, it is established that the mean annual rate of structural failure should be less than or equal to a certain prescribed value. The LCC of the structure includes 1) initial cost, 2) cost due to damages, and 3) social costs. The methodology is applied for two sets of reinforced concrete buildings; the first set is located on firm ground and the second on soft soil. The reinforced concrete buildings are designed using different load combination factors, and the total expected cost is estimated for each set of buildings. It is concluded that the optimal load combination factors for the buildings on soft soil are different from that obtained on firm ground. Finally, some recommendations are provided to estimate the seismic load factors for structures located at firm and soft soils.

Applications of total expected cost concept to various decision making situations

The probabilistic safety measure has been common among structural engineers. Optimum Load factors based on the minimization of total expected cost were proposed in 1991. Applications of the total cost concept were developed for occasions of safety decision making. CO2 emission can be used as an alternative scale to the monetary cost. Optimal seawall height against Tsunami was another example.

Estimation of economic damage in the difference of the transformer loading factor

The article considers a method to determine the optimal load of a power transformer. A method for estimation economic damage in case of deviation of the load factor of the transformer has been developed. According to the proposed method, the optimal load factor of the power transformer was determined according to the criterion of the minimum cost of money for the transformation of electric energy. The load level of power transformers can be estimated by two criteria, i.e., by the maximum integral value of the efficiency and by the minimum loss of funds during the transformation of electricity. According to the proposed methodology, the damage was estimated when the load factor of the transformer deviated from the optimal values. For this, the relative losses of electrical energy were calculated. The results obtained, from the point of view of energy and financial and economic efficiency, show that when the load factor is overestimated relative to the optimal values, it is much more preferable to overestimate them than to underestimate them.

Efficiency Analysis and Improvement of an Intelligent Transportation System for the Application in Greenhouse

In view of the future lack of human resources due to the aging of the population, the automatic, Intelligent Mechatronic Systems (IMSs) and Intelligent Transportation Systems (ITSs) have broad application prospects. However, complex application scenarios and limited open design resources make designing highly efficient ITS systems still a challenging task. In this paper, the optimal load factor solving solution is established. By converting the three user requirements including working distance, time and load into load-related factors, the optimal result can be obtained among system complexity, efficiency and system energy consumption. A specialized visual navigation and motion control system has been proposed to simplify the path planning, navigation and motion control processes and to be accurately calculated in advance, thereby further improving the efficiency of the ITS system. The validity of the efficiency calculation formula and navigation control method proposed in this paper is verified. Under optimal conditions, the actual working mileage is expected to be 99.7%, and the energy consumption is 83.5% of the expected value, which provides sufficient redundancy for the system. In addition, the individual ITS reaches the rated operating efficiency of 95.86%; in other words, one ITS has twice the ability of a single worker. This proves the accuracy and efficiency of the designed ITS system.

Artificial Noise Injection and Its Power Loading Methods for Secure Space-Time Line Coded Systems.

In this paper, we consider a space-time line coded (STLC) system having two-transmit and two-receive antennas. To improve the secrecy rate of the STLC system, in which an illegitimate receiver eavesdrops the information delivered from the STLC transmitter to the STLC receiver, we propose an artificial noise (AN) injection method. By exploiting the STLC structure, a novel AN for the STLC is designed and its optimal power loading factor is derived. Numerical results verify that the proposed secure STLC systems with the designed AN injection and the power control method can significantly improve the secrecy rate compared to the conventional STLC systems. It is observed that the proposed method is more effective if there is a significant gap between the main-channel and the eavesdropper-channel gains.

A Robust Capon Beamforming Approach for Sparse Array Based on Importance Resampling Compressive Covariance Sensing

Reconstructing the interference-plus-noise covariance matrix instead of searching for the optimal diagonal loading factor for the sample covariance matrix is a good method for calculating the adaptive beamforming coefficients. However, when the directions-of-arrival (DOAs) and the number of the interferences are unknown and the steering vector has an error, the reconstructed interference-plus-noise covariance matrix might not be accurate, which degrades the performance of adaptive beamforming. Here, we propose a robust Capon beamforming approach, which is suited to the sparse array with the array steering error and the unknown interference DOAs. In particular, by drawing a modified optimization problem and the mean shift model of the interference covariance matrix, we propose the robust beamforming with the importance resampling based compressive covariance sensing, which is shown to outperform the classical beamforming method based on reconstructing the interference-plus-noise covariance matrix. The key to our approach is the new solution of the reconstructing method and the important functions. The excellent performance of the proposed approach for interference suppression is demonstrated via a number of numerical examples.

Modified Robust Capon Beamforming with Approximate Orthogonal Projection onto the Signal-Plus-Interference Subspace

In this paper, a new robust adaptive beamforming technique based on a modification of the robust Capon beamforming approach is introduced. It is shown that this technique leads to an approximate eigenspace projection-based array steering vector estimation. The steering vector is estimated as an approximation for the orthogonal projection of the presumed steering vector of the desired signal onto the signal-plus-interference subspace. Also, it is demonstrated that the optimal diagonal loading factor corresponds to the minimum of the estimated beamformer output power. Furthermore, the formulation of the proposed method provides the possibility of estimating the direction-of-arrival of the desired signal. This estimation is then used to update the presumed steering vector. An important virtue of the proposed method is its better or comparable performance with less computational complexity than the recent existing methods.

Reliability-based optimal load factors for seismic design of buildings

A reliability-based development of load factors for the combination of seismic and gravity loads is presented. The procedure aims at minimizing the total expected life-cycle cost of buildings, having as a constraint a maximum value of the mean annual failure rate. The loads considered are dead, live and earthquake loads. The methodology is applied to a large inventory of reinforced concrete frames and steel frames buildings located at a soft soil region of Mexico City. Artificial Neural Networks are used to efficiently obtain the designs and the reliabilities of the buildings in the inventory. For the range of load combinations studied, the optimal load factors were found to be insensitive to the value of life, but sensitive to the fundamental vibration period of the structures.

Comparison of Two Volatile Sampling Techniques Based on Different Loading Factors in Determination of Volatile Organic Compounds Released from Spoiled Raw Beef

Evaluation of meat volatiles is an increasing concern due to the development studies for spoilage sensors in order to inform consumers if meat spoiled or not. Since the reliable measuring of volatiles in headspace is important for designing a sensor, preconcentration techniques for meat matrix should be investigated. This study describes the effect of three sample amounts: total volume ratio (loading factors) with 0.025, 0.05, and 0.10 kg/L applied in two preconcentration sampling techniques: solid phase microextraction (SPME) and gas flushing on Tenax with thermal desorption to explain the interactions and relationship between sample amount and extracted analytes for spoiled beef striploin. The ratio of the sample amount of beef meat in the chamber and the total volume of chamber is called as “loading factor”. The results showed that the volatile profiles did not vary significantly, but the levels were affected with the extraction technique and loading factor. The volatile organic compounds identified in the early stages of meat spoilage include alcohols, aldehydes, ketones, esters, and amine compounds. While amines were measured only with Tenax, ethyl acetate was detected only with SPME. The total peak area of volatiles with Tenax (~390 × 10−6 AU at 0.05 kg/L) were higher than SPME sampling (~290 × 10−6 AU at 0.05 kg/L) in each loading factor. Although optimum loading factor depended on the type of volatile, 0.05 kg/L loading factor resulted the most efficient extraction by the two preconcentration techniques for most of the volatiles generally.

A Stochastic Analysis of Network MIMO Systems

This paper quantifies the benefits and limitations of cooperative communications by providing a statistical analysis of the downlink in network multiple-input multiple-output (MIMO) systems. We consider an idealized model where the multiple-antenna base-stations (BSs) are distributed according to a homogeneous Poisson point process and cooperate by forming disjoint clusters. We assume that perfect channel state information (CSI) is available at the cooperating BSs without any overhead. Multiple single-antenna users are served using zero-forcing beamforming with equal power allocation across the beams. For such a system, we obtain tractable, but accurate, approximations of the signal power and inter-cluster interference power distributions and derive a computationally efficient expression for the achievable per-BS ergodic sum rate using tools from stochastic geometry. This expression allows us to obtain the optimal loading factor, i.e., the ratio between the number of scheduled users and the number of BS antennas, that maximizes the per-BS ergodic sum rate. Further, it allows us to quantify the performance improvement of network MIMO systems as a function of the cooperating cluster size. We show that to perform zero-forcing across the distributed set of BSs within the cluster, the network MIMO system introduces a penalty in received signal power. Along with the inevitable out-of-cluster interference, we show that the per-BS ergodic sum rate of a network MIMO system does not approach that of an isolated cell even at unrealistically large cluster sizes. Nevertheless, network MIMO does provide significant rate improvement as compared to uncoordinated single-cell processing even at relatively modest cluster sizes.