scholarly journals Analytical Models to Characterize Trade-Offs between Technological Upgrading and Innovation

2022 ◽  
Vol 9 (1) ◽  
pp. 0-0
Keyword(s):  
Capital Investment ◽  
Optimal Allocation ◽  
Planning Process ◽  
Profit Maximization ◽  
Analytical Models ◽  
Environmental Compliance ◽  
Compliance Cost ◽  
Predator Prey Model ◽  
Trade Offs ◽  
Allocation Process

We propose two analytical models to characterize the relationship between technological upgrading and innovation in the oil & gas industry. The first one is an “optimization model” which focuses on the trade-offs between profit maximization and environmental compliance cost. The other has been developed based on “predator-prey” model which captures the dynamics of biological systems. Our study contributes to the strategic planning process for sustainable development by providing the insight that optimal allocation process is determined by multiple operational factors, including a firm’s competitive ranking among its industrial competitors, industrial consent on the concurrent rate of return on capital investment, the projected demand of oil & gas in future, and a change in environmental compliance cost. Further, we add to the robustness of the optimal allocation process by providing binding conditions of the set of solutions.

Performance Impacts of Tailored Surface Geometry in Li-Ion Battery Cathodes

2013 ◽  
Author(s):  
George J. Nelson
Keyword(s):  
Surface Area ◽  
Solid Phase ◽  
Particle Surface ◽  
Surface Characteristics ◽  
Analytical Models ◽  
Li Ion Battery ◽  
Fractal Structures ◽  
Surface Geometry ◽  
Trade Offs ◽  
Li Ion

Analytical models developed to investigate charge transfer in Li-ion battery cathodes reveal distinct transport regimes where performance may be limited by either microstructural surface characteristics or solid phase geometry. For several cathode materials, particularly those employing conductive additives, surface characteristics are expected to drive these performance limitations. For such electrodes gains in performance may be achieved by modifying surface geometry to increase surface area. However, added surface area may present a diminishing return if complex structures restrict access to electrochemically active interfaces. A series of parametric studies has been performed to better ascertain the merits of complex, tailored surfaces in Li-ion battery cathodes. The interaction between lithium transport and surface geometry is explored using a finite element model in which complex surfaces are simulated with fractal structures. Analysis of transport in these controlled structures permits assessment of scaling behavior related to surface complexity and provides insight into trade-offs in tailoring particle surface geometry.

Characterization of a soft magnetic composite for use in road-embedded wireless-charging systems

2021 ◽  
pp. 1-10
Author(s):  
Kai-Yeung Li ◽  
Bill Trompetter ◽  
Maedeh Amirpour ◽  
Tom Allen ◽  
Simon Bickerton ◽  
...  
Keyword(s):  
Volume Fraction ◽  
Flexural Modulus ◽  
Magnetic Core ◽  
Analytical Models ◽  
Magnetic Composite ◽  
Wireless Charging ◽  
Soft Magnetic ◽  
Soft Magnetic Composite ◽  
Trade Offs ◽  
Wheel Loading

The ferrite magnetic core is an integral component of road-embedded wireless charging systems for electric vehicles. However, the brittleness of ferrite makes it susceptible to premature fracture due to cyclic wheel loading from vehicles. This has motivated the development of a soft magnetic composite (SMC) composed of a flexible polyurethane and crushed ferrite as an alternative. An experimental investigation was conducted into the trade-offs between mechanical, thermal and magnetic properties at ferrite volume fractions between 45.9[Formula: see text]vol% and 80.6[Formula: see text]vol%. A comparison was made between measured properties and predictions from analytical models in order to further investigate the characteristics of the composite. The investigation showed a trade-off between the increase in magnetic permeability and the reduction in strain-to-failure as ferrite volume fraction increased. In addition, a large increase in flexural modulus and thermal conductivity, along with a slight increase in flexural strength was observed. More importantly, the strain-to-failure of the composite was 20 times higher than that of ferrite even at the highest volume fraction, indicating that the SMC was successful in providing a more ductile and flexible alternative.

scholarly journals Determining Equipment Capacity of Electric Vehicle Charging Station Operator for Profit Maximization

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2301 ◽  
Author(s):  
Se Baik ◽  
Young Jin ◽  
Yong Yoon
Keyword(s):  
Capital Investment ◽  
Storage System ◽  
Profit Maximization ◽  
Energy Storage System ◽  
Auxiliary Equipment ◽  
Charging Infrastructure ◽  
Physical Constraints ◽  
Charging Station ◽  
Study Results ◽  
Ev Charging

Related to global efforts to reduce greenhouse gases, numerous electric vehicles (EVs) are expected to be integrated to the power grid. However, the introduction of EVs, particularly in Korea, is still marginal due to the lack of EV charging infrastructure, even though various supportive policies exist. To address this shortage of EV charging stations, the EV charging business needs to be profitable. As with any business, the profitability of the EV charging business is significantly affected by the initial capital investment related to EV chargers and auxiliary equipment such as power conditioning system (PCS), battery energy storage system (BESS), and on-site photovoltaic (PV) generation system. Thus, we propose a formulation to determine the number of EV chargers and the capacity of auxiliary equipment with the objective of a charging station operator (CSO) maximizing profit under regulatory, economic, and physical constraints. The effectiveness of the proposed method is verified with simulations considering various EV charging patterns. The study results will help improve the EV charging infrastructure by encouraging individuals and companies to participate in EV charging business.

scholarly journals Study on Profitable Shared Parking Management Based on Day-to-Day Evolution Model

2021 ◽  
Vol 33 (1) ◽  
pp. 17-33
Author(s):  
Duo Xu ◽  
Huijun Sun
Keyword(s):  
Urban Area ◽  
Optimal Allocation ◽  
Cost Minimization ◽  
Profit Maximization ◽  
Evolution Model ◽  
Residential Areas ◽  
Short Supply ◽  
Parking Lots ◽  
Morning Commute ◽  
Quantity Control

Parking problems are getting increasingly serious in the urban area. However, the parking spots in the urban area are underutilized rather than really scarce. There is a large number of private spots in the residential areas that have the potential of being shared. Due to its private nature, shared parking is usually operated by a profitable mode. To study the utilization of shared parking and its impact on the morning commute, this paper proposes an evolution model. The supply side is a profit-chasing manager who decides on the selling prices and the business scale, while the demand side refers to travellers who respond to costs and choose the trip mode. By analysing the behaviour (strategy) of both sides, the study covers: 1 - the attraction and competition between parking lots and trip modes, 2 - the utilization and user composition of the parking lots. By inducing two numerical examples, the conclusions are that 1 - managers can achieve maximum profit and optimal allocation through price adjustment and quantity control; 2 - publicity (system cost minimization) and profitability (profit maximization) are consistent under certain threshold conditions; 3 - competition exists between parking lots as well as trip modes; some parking lots are even in short supply; profitable management does not create a market monopoly.

scholarly journals Optimum Manpower Allocation in Health Care Using Statistical Process Control

2019 ◽  
pp. 1-9
Author(s):  
William E. Odinikuku ◽  
Jephtah A. Ikimi ◽  
Ikechukwu P. Onwuamaeze
Keyword(s):  
Health Care ◽  
Process Control ◽  
Statistical Process Control ◽  
Optimal Allocation ◽  
Manpower Planning ◽  
Production Costs ◽  
Statistical Control ◽  
Statistical Process ◽  
Planning Models ◽  
Allocation Process

In many countries manpower problems in the field of health care are regular items on the agenda of policy makers. To avoid mismatches between demand of care and supply of care on national and regional levels, manpower planning models and methods are used to determine adequate numbers of medical specialists to fulfill the future demand of care. Inadequate or inefficient allocation of manpower to various departments in an organization or workplace can lead to undesired outcomes which may include: down time, reduced productivity, workers fatigue, increased production costs, etc. As a result of the above stated problem, there is need to devise a statistical model that will ensure optimal allocation of manpower. In this study, the optimum allocation of two hundred and fifty two general nurses to fifteen wards at a hospital code named WCH located in South-South geopolitical zone, Nigeria was achieved using statistical process control. The study involved the analysis of data obtained from our hub of study for a period of two months. The C-chart was used to check if the process of allocation was in control or not. The result obtained from the study showed that the manpower allocation process was out of statistical control as the allocation of the children emergency ward was outside the upper control limit of the c-chart plot.

scholarly journals Optimizing Discount and Reputation Trade-Offs in E-Commerce Systems: Characterization and Online Learning

2019 ◽  
Vol 33 ◽  
pp. 7992-7999 ◽  
Author(s):  
Hong Xie ◽  
Yongkun Li ◽  
John C. S. Lui
Keyword(s):  
Learning Algorithm ◽  
Profit Maximization ◽  
Projection Algorithm ◽  
Reputation Systems ◽  
Maximization Problem ◽  
Transaction Data ◽  
Q Learning ◽  
Price Discounts ◽  
Trade Offs ◽  
Forward Projection

Feedback-based reputation systems are widely deployed in E-commerce systems. Evidences showed that earning a reputable label (for sellers of such systems) may take a substantial amount of time and this implies a reduction of profit. We propose to enhance sellers’ reputation via price discounts. However, the challenges are: (1) The demands from buyers depend on both the discount and reputation; (2) The demands are unknown to the seller. To address these challenges, we first formulate a profit maximization problem via a semiMarkov decision process (SMDP) to explore the optimal trade-offs in selecting price discounts. We prove the monotonicity of the optimal profit and optimal discount. Based on the monotonicity, we design a QLFP (Q-learning with forward projection) algorithm, which infers the optimal discount from historical transaction data. We conduct experiments on a dataset from to show that our QLFP algorithm improves the profit by as high as 50% over both the classical Q-learning and speedy Q-learning algorithm. Our QLFP algorithm also improves the profit by as high as four times over the case of not providing any price discount.

scholarly journals The evolutionary convergence of avian lifestyles and their constrained coevolution with species' ecological niche

2015 ◽  
Vol 282 (1821) ◽  
pp. 20151808 ◽  
Author(s):  
Paola Laiolo ◽  
Javier Seoane ◽  
Juan Carlos Illera ◽  
Giulia Bastianelli ◽  
Luis María Carrascal ◽  
...  
Keyword(s):  
Life Histories ◽  
Ecological Niche ◽  
Optimal Allocation ◽  
Reproductive Investment ◽  
Cost Of Reproduction ◽  
Phenotypic Evolution ◽  
Realized Niche ◽  
Trade Offs ◽  
The Cost ◽  
Species Variability

The fit between life histories and ecological niche is a paradigm of phenotypic evolution, also widely used to explain patterns of species co-occurrence. By analysing the lifestyles of a sympatric avian assemblage, we show that species' solutions to environmental problems are not unbound. We identify a life-history continuum structured on the cost of reproduction along a temperature gradient, as well as habitat-driven parental behaviour. However, environmental fit and trait convergence are limited by niche filling and by within-species variability of niche traits, which is greater than variability of life histories. Phylogeny, allometry and trade-offs are other important constraints: lifetime reproductive investment is tightly bound to body size, and the optimal allocation to reproduction for a given size is not established by niche characteristics but by trade-offs with survival. Life histories thus keep pace with habitat and climate, but under the limitations imposed by metabolism, trade-offs among traits and species' realized niche.

Implementation of Population Algorithms to Minimize Power Losses and Cable Cross-Section in Power Supply System

2016 ◽  
Vol 6 (6) ◽  
pp. 2955 ◽  
Author(s):  
V. Z. Manusov ◽  
P. V. Matrenin ◽  
E. S. Tretiakova
Keyword(s):  
Cross Section ◽  
Cross Sections ◽  
Capital Investment ◽  
Optimal Allocation ◽  
Reactive Power ◽  
Active Power ◽  
Power Losses ◽  
Power Sources ◽  
First Case ◽  
Active Power Losses

<p><span lang="EN-US">The article dues to the arrangement of the reactive power sources in the power grid to reduce the active power losses in transmission lines and minimize cable cross-sections of the lines. The optimal arrangement is considered from two points of view. In the first case, it is possible to minimize the active power losses only. In the second case, it is possible to change the cross-sections of the supply lines to minimize both the active power losses and the volume of the cable lines. The sum of the financial cost of the active power losses, the capital investment to install the deep reactive power compensation, and cost of the cable volume is introduced as the single optimization criterion. To reduce the losses, the deep compensation of reactive power sources in nodes of the grid are proposed. This optimization problem was solved by the Genetic algorithm and the Particle Swarm optimization algorithm. It was found out that the deep compensation allows minimizing active power losses the cable cross-section. The cost-effectiveness of the suggested method is shown. It was found out that optimal allocation of the reactive power sources allows increasing from 9% to 20% the financial expenses for the enterprise considered.</span></p>

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