Initial Cut Research Articles

An experimental investigation on surface integrity and wire wear in rough and trim cut modes of WEDM for hybrid composite

PurposeThe purpose of this paper is to investigate the surface integrity features, including surface roughness (SR), recast layer (RL), material migration, topography and wire wear pattern in rough and trim-cut wire electric discharge machine (WEDM) of hybrid composite (Al6061-90%/SiC-2.5%/TiB2-7.5%).Design/methodology/approachEffects of four important factors, namely, rough-cut history (RCH), pulse on time (Ton), peak current (IP) and wire offset (WO) have been assessed on the responses of interest for trim-cut WEDM. Box–Behnken design (RSM) was used to formulate the experimentation plan. Quantitative indices of surface integrity, namely, SR and RL, and selected samples have been investigated for qualitative analysis, namely, surface topography, material migration and wire wear pattern.FindingsTon and IP are found to be most significant, whereas RCH and WO are found insignificant for SR. Ton and WO were found to be the most significant factors affecting RL. After trim cut, an RL of thickness 8.26 µm is observed if the initial rough cut has been accomplished at high discharge energy setting. Whereas the best value of RL thickness, i.e. 5.36 µm, can be realized with low level of RCH. A significant decrease in the presence of foreign materials is recorded, indicating its strong correlation with the discharge energy used during machining.Originality/valueInvestigation on surface integrity features for machining of hybrid composite through rough and trim-cut WEDM has been reported by only a limited number of researchers in the past. This study is attempted at fulfilling few vital gaps by addressing the issues such as evaluation of the efficacy of trim cutting under different discharge energy conditions (using RCH), analysis of wire wear pattern in both rough and trim-cut modes and investigation of the wire breakage phenomenon during machining.

Simulation of the thermal field in reservoir during the filtration of live oil and water with considering the heat of oil degassing and thermodynamic effects

In the process of water invasion of reservoir under conditions of pressure decrease below the bubble point pressure of oil with dissolved gas, when oil degasses, an area of three-phase flow of oil, water and gas appears in the reservoir. In this case, each of the phases makes a certain contribution to the formation of the thermal field in the reservoir, due to the thermodynamic effects shows and the heat of oil degassing. The thermal field forming is influence many parameters, for example, the initial water cut of formation, gas oil ratio, the ratio of reservoir pressure and bubble point pressure of oil with dissolved gas, the ratio of reservoir pressure and bottomhole pressure, etc. The thermohydrodynamic processes occurring in this case carry information about the formation and the near wellbore zone. One of the directions for using the features of the formation of the temperature field in this case is the use of thermometric studies of wells to diagnose the condition of the well and formation. Reservoir water invasion under the condition of oil degassing leads to a change in the temperature distribution in the formation, which can be used in diagnosing the identifying sources of water invasion. Using a numerical method for solving the equations of mass conservation and heat influx during non-isothermal three-phase filtration, in this work are studied the features of the formation of the temperature field in an oil-saturated reservoir with an initial water cut during oil degassing. As a result of calculations for various ratios of the initial water cut of the formation and the gas oil ratio, temperature dependences were obtained for different of well operation times. The obtained dependences of temperature on water cut and gas oil ratio can be used as palettes for quantitative evaluation of water inflow rates from formations.

Benders decomposition algorithms for minimizing the spread of harmful contagions in networks

The COVID-19 pandemic has been a recent example for the spread of a harmful contagion in large populations. Moreover, the spread of harmful contagions is not only restricted to an infectious disease, but is also relevant to computer viruses and malware in computer networks. Furthermore, the spread of fake news and propaganda in online social networks is also of major concern. In this study, we introduce the measure-based spread minimization problem (MBSMP), which can help policy makers in minimizing the spread of harmful contagions in large networks. We develop exact solution methods based on branch-and-Benders-cut algorithms that make use of the application of Benders decomposition method to two different mixed-integer programming formulations of the MBSMP: an arc-based formulation and a path-based formulation. We show that for both formulations the Benders optimality cuts can be generated using a combinatorial procedure rather than solving the dual subproblems using linear programming. Additional improvements such as using scenario-dependent extended seed sets, initial cuts, and a starting heuristic are also incorporated into our branch-and-Benders-cut algorithms. We investigate the contribution of various components of the solution algorithms to the performance on the basis of computational results obtained on a set of instances derived from existing ones in the literature.

Taking the human out of decomposition-based optimization via artificial intelligence, Part II: Learning to initialize

The repeated solution of large-scale optimization problems arises frequently in process systems engineering tasks. Decomposition-based solution methods have been widely used to reduce the corresponding computational time, yet their implementation has multiple steps that are difficult to configure. We propose a machine learning approach to learn the optimal initialization of such algorithms which minimizes the computational time. Active and supervised learning is used to learn a surrogate model that predicts the computational performance for a given initialization. We apply this approach to the initialization of Generalized Benders Decomposition for the solution of mixed-integer model predictive control problems. The surrogate models are used to find the optimal initialization, which corresponds to the number of initial cuts that should be added in the master problem. The results show that the proposed approach can lead to a significant reduction in solution time, and active learning can reduce the data required for learning.

Response of consumers to wage shocks in the framework of the Portuguese assistance program

AbstractThis paper studies the impact on consumption of the exogenous changes in public wages in Portugal during and after the economic and financial assistance program (2011-2014), by exploiting the variability in the size of such changes across municipalities. The initial wage cuts triggered a marked reduction of private consumption, while the reinstatements in the later years gave rise to an increase, albeit of a smaller magnitude. The consumption response was larger for employees with relatively lower wages. Households smoothed the impact on consumption of negative income shocks partly by drawing down their deposits. Consumer credit did not play such a role, as households deleveraged as a response to those negative shocks.

Combining silicon, organic matter, and Trichoderma harzianum to mitigate salt stress in forage sorghum

Salt stress is a major abiotic factor limiting plant growth worldwide, particularly in arid and semiarid regions where excessive groundwater use in irrigation leads to high salt concentrations. To address this issue, this study investigated the efficacy of silicon, either alone or in combination with Trichoderma harzianum and organic matter, in mitigating salt stress in forage sorghum. The experiment took place in a saline Fluvisol in Parnamirim, a semiarid region of Pernambuco, Brazil, and followed a randomized block design with five treatments and four replicates: sorghum (control); sorghum + Si; sorghum + Si + OM (organic matter); sorghum + Si + T (T. harzianum); and sorghum + Si + T + OM. Sorghum plants were assessed over three cycles (initial cut and two regrowths) from June 2021 to April 2022. The combined treatments of Si + OM, Si + T, and Si + T + OM increased plant growth by 42.17, 35.49, and 27.51%, respectively, compared to the control. Similarly, these treatments led to biomass accumulation gains of 39.42, 40.44, and 31.77% in sorghum plants relative to the control. Silicon alone did not yield significant growth or biomass accumulation improvements. The application of silicon in conjunction with T. harzianum and/or organic matter shows promise in enhancing forage sorghum growth under saline stress conditions in semiarid regions.

The Economic Evaluation of Various Production Scenarios for Zubair Reservoir in the Kifl Field

This work evaluates the economic feasibility of various production scenarios for the Zubair reservoir in the Kifl oil field using cash flow and net present value (NPV) calculations. The Kifl field is an exploratory field that has not yet been developed or assessed economically. The first well was drilled in 1960, and three other wells were later drilled to assess the oil accumulation, so in this research, Different production scenarios were evaluated economically. These scenarios were proposed based on the reservoir model of the Zubair formation in the field. The research methodology used QUE$TOR software to estimate capital expenditures (CapEx) and operating expenditures (OpEx) based on field-level data, production profiles for each scenario, and produced fluid properties. CapEx estimates were mainly based on the number of drilled wells and plateau duration, while OpEx estimates were based on the number of barrels produced from each scenario. Cash flow values were estimated each year in the production interval after subtracting water handling costs, CapEx, and OpEx from the gross revenue of oil produced. The NPV for each scenario was then calculated using a 5% interest rate, and the most economical option was determined by comparing the NPV values of each scenario. Case-3 scenario was identified as the most economical option, with a high NPV value of approximately 612 MM$, an oil production rate of 10 MSTB/d, a Plateau duration of 3 years, a total number of wells of 11, and an Initial water cut of 13 %.

New well water cut prediction using machine learning

Background: The drilling of new wells is one of the most effective geological and technical activities. In mature fields characterized by high production of reserves and high water availability, the selection of design points for drilling is a difficult task. Forecasting the parameters of new wells is possible by using geological and hydrodynamic models or analytical methods. In this paper, the authors propose the use of machine learning algorithms to predict the initial parameters of new wells based on an extensive set of geological and field data.
 Aim: The article describes the process of developing machine learning algorithms and demonstrates the performance indicators of a complex model. As part of this work, testing of machine learning algorithms was performed to predict the start-up water cut of potential candidates.
 Materials and methods: Within the framework of this work, various machine learning methods were applied on geological and technical field data.
 Results: The developed complex model showed acceptable convergence results based on classification and regression metrics, which indicates its applicability for predicting the start-up water cut of project wells.
 Conclusion: This method of predicting indicators is an alternative tool for predicting the start-up water cut of new wells, which makes it possible to clarify and supplement the forecast parameters calculated using a geological and hydrodynamic model or empirical dependencies of the initial water cut of new wells on geological parameters.

Accelerating Benders decomposition approach for shared parking spaces allocation considering parking unpunctuality and no-shows

By allocating idle private parking spaces to demanders, shared parking reuses idle resources and effectively alleviates parking problems. In practice, there may be parking unpunctuality behavior of demanders, as well as the potential no-show behavior of owners and demanders. These stochastic factors affect the allocation of shared parking spaces. In this paper, we study the shared parking spaces allocation problem considering parking unpunctuality and no-shows. First, the allocation problem considering parking unpunctuality is formulated as a stochastic programming model, with the objective to maximize the profit of the shared parking platform. Sample average approximation (SAA) combined with an accelerating Benders decomposition (ABD) algorithm is exploited to solve the model effectively, where initial optimality cuts are explored to speed up the convergence of the algorithm. Then the proposed approach is extended to incorporate no-shows. Numerical experiments show great performance of the proposed approach. The experiments also show that the fluctuations of the unpunctual time and the no-show probability have a significant impact on the shared parking system, and balanced supply and demand is helpful to increase the profit of the platform and the satisfaction of demanders.

Effect of Cutting Dates on Forage Yield of Three Vicia Varieties (Vicia Spp.) in Sulaimani Governorate.

During the winter season of 2021-2022, a field experiment was conducted at Qlyasan locations in Sulaimani governorate. The aim of this research was to examine the consequence of cutting dates on the yield of forage and seeds, as well as on the components of various Vicia varieties. The experiment was designed as a factorial design and conducted using a randomized complete block design. The least significant difference (L.S.D.) test with a significance level of 5% was used for the statistical analysis. The three Vicia varieties tested were common vetch (Vicia sativa), narbon vetch (Vicia narbonensis), and bitter vetch (Vicia ervilia). Two cutting dates were used, namely, control (Co, no cut), cut 1 (80 days after sowing), and cut 2 (20 days after the first cut). The findings of this research demonstrated that the interaction between common vetch and cutting at 80 days after sowing produced the highest values of the dry matter percentage trait. Meanwhile, the interaction between narbon vetch and cutting 20 days following the initial cut produced the maximum fresh yield (ton/ha) and stem dry weight (g) values. The highest recorded values for the characteristics "pod count per plant" and "seed yield (kg/ha)" were obtained through the interaction between the control treatment and narbon vetch. However, the interaction between cutting at 80 days after sowing and narbon vetch produced the highest values of the 100-seed weight trait (gm). The variation in climatic conditions between seasons may explain these results.

Economic Evaluation Of Water Production Management With Rpm (Relative Permability Modifier) Treatment Based On Gross Split Contract In “Re” Well In “Dn" Field

The "RE" well in the "DN" field is an oil well produced in June 2004 with an initial water cut value of 15% as time went on there was a fairly high increase in the water cut value reaching 97% which means that it caused increased water production. and oil production decreased from 387 BOPD to 11 BOPD.
 Appropriate handling in overcoming excessive water production, one of which is by using a method that can selectively restrain water production without restraining hydrocarbon production with RPM (Relative Permeability Modifier) ​​Treatment. RPM (Relative Permeability Modifier) ​​is a type of polymer with a high molecular weight as the main molecule of RPM. RPM can be done without isolating the layer zone so that it can be injected bullhead into all layer zones to reduce water permeability.
 This final project research has been seen from increasing the rate of oil production and decreasing the water cut. The selected well is the "RE" well in the "DN" field which has an increasing water cut value and decreased oil production. Then calculate the economy using the gross split method to calculate the feasibility level of the RPM (Relative Permeability Modifier) ​​Treatment project.

Pareto-Improving Optimal Capital and Labor Taxes

We study optimal fiscal policy in a model with agents who are heterogeneous in their labor productivity and wealth, and there is an upper bound on the capital tax rate each period. We focus on Pareto-improving plans. We show that the optimal tax reform is to cut labor taxes and leave capital taxes high in the short and medium run. Only in the very long run would capital taxes be zero. For our calibration labor taxes should be low for the first eleven to twenty-six years, while capital taxes should be at their maximum. This policy ensures that all agents benefit from the tax reform and that capital grows quickly after the reform. Therefore, the long-run optimal tax mix is the opposite of the short- and medium-run one. The initial labor tax cut is financed by deficits, which lead to a positive level of government debt in the long run, reversing the standard prediction that the government accumulates savings in models with optimal capital taxes. The welfare benefits from the tax reform are high and can be shifted entirely to capitalists or workers by varying the length of the transition.

Digital twin of a continuous chromatography process for mAb purification: Design and model-based control.

Model-based design of integrated continuous train coupled with online process analytical technology (PAT) tool can be a potent facilitator for monitoring and control of Critical Quality Attributes (CQAs) in real time. Charge variants are product related variants and are often regarded as CQAs as they may impact potency and efficacy of drug. Robust pooling decision is required for achieving uniform charge variant composition for mAbs as baseline separation between closely related variants is rarely achieved in process scale chromatography. In this study, we propose a digital twin of a continuous chromatography process, integrated with an online HPLC-PAT tool for delivering real time pooling decisions to achieve uniform charge variant composition. The integrated downstream process comprised continuous multicolumn capture protein A chromatography, viral inactivation in coiled flow inverter reactor (CFIR), and multicolumn CEX polishing step. An online HPLC was connected to the harvest tank before protein A chromatography. Both empirical and mechanistic modeling have been considered. The model states were updated in real time using online HPLC charge variant data for prediction of the initial and final cut point for CEX eluate, according to which the process chromatography was directed to switch from collection to waste to achieve the desired charge variant composition in the CEX pool. Two case studies were carried out to demonstrate this control strategy. In the first case study, the continuous train was run for initially 14 h for harvest of fixed charge variant composition as feed. In the second case study, charge variant composition was dynamically changed by introducing forced perturbation to mimic the deviations that may be encountered during perfusion cell culture. The control strategy was successfully implemented for more than ±5% variability in the acidic variants of the feed with its composition in the range of acidic (13%-17%), main (18%-23%), and basic (59%-68%) variants. Both the case studies yielded CEX pool of uniform distribution of acidic, main and basic profiles in the range of 15 ± 0.8, 31 ± 0.3, and 53 ± 0.5%, respectively, in the case of empirical modeling and 15 ± 0.5, 31 ± 0.3, and 53 ± 0.3%, respectively, in the case of mechanistic modeling. In both cases, process yield for main species was >85% and the use of online HPLC early in the purification train helped in making quicker decision for pooling of CEX eluate. The results thus successfully demonstrate the technical feasibility of creating digital twins of bioprocess operations and their utility for process control.

RESEARCH AND IMPROVEMENT OF OIL FIELD DEWATERING

A steady increase in the water content of the extracted oil, an increase in the volume of heavy grades of oil with stable emulsions, an increase in the proportion of thick oil in the total volume of refined oil due to the imperfection of the oil dewatering process is far from a complete list of factors determining the importance and relevance of the issue of optimal automatic control of the oil dewatering process in the fields today. Although this problem is not new to the oil industry, its solution is not yet completed. This circumstance is due to insufficient knowledge of the processes of oil preparation due to the emerging objective difficulties and the lack of adequate models that could be used to solve the problems of stabilization and optimization of the oil dewatering process. The paper presents the research on the process of breaking highly-stable heavy oil emulsions by water evaporation. An equation has been derived and relevant curves have been plotted to calculate the required heating temperature. This study shows the dependence of hydrocarbon distillate yield on heating temperature, boiling point oil composition and the initial water cut of the emulsion. The technology of oil dehydration from the field has been tested.

Pattern Generation for Three Dimensional Cutting Stock Problem

We consider the problem of three-dimensional cutting of a large block that is to be cut into some small block pieces, each with a specific size and request. Pattern generation is an algorithm that has been used to determine cutting patterns in one-dimensional and two-dimensional problems. The purpose of this study is to modify the pattern generation algorithm so that it can be used in three-dimensional problems, and can determine the cutting pattern with the minimum possible cutting residue. The large block will be cut based on the length, width, and height. The rest of the cuts will be cut back if possible to minimize the rest. For three-dimensional problems, we consider the variant in which orthogonal rotation is allowed. By allowing the remainder of the initial cut to be rotated, the dimensions will have six permutations. The result of the calculation using the pattern generation algorithm for three-dimensional problems is that all possible cutting patterns are obtained but there are repetitive patterns because they suggest the same number of cuts.

E-commerce supply chain network design using on-demand warehousing system under uncertainty

During the COVID-19 pandemic, e-commerce retailers have had trouble satisfying the growing demand because of limited warehouse capacity constraints. Fortunately, an on-demand warehousing system has emerged as a new alternative to mitigate warehouse capacity issues. In recent years, several studies have focused on the supply chain problem considering on-demand warehousing. However, there is no study that deals simultaneously with inherent uncertainties and the property of commitment, which is the main advantage of on-demand warehousing. To fill these research gaps, this paper presents an e-commerce supply chain network design problem considering an on-demand warehousing and decisions for commitment periods. We propose the two-stage stochastic programming model that captures the inherent uncertainties to formulate the presented problem. We solve the proposed model utilizing sample average approximation combined with the Benders decomposition algorithm. Of particular note, we develop a method to generate effective initial cuts for improving the convergence speed of the Benders decomposition algorithm. Computational results show that the developed method could find an effective feasible solution within a reasonable computational time for problems of practical size. Furthermore, we show the significant cost-saving effects, based on experiment results, that occur when an on-demand warehousing system is used for designing supply chain networks.

Unrelated parallel machine scheduling problem with special controllable processing times and setups

The controllable processing times (CPTs) have many practical applications, enabling the length of the job processing to vary within an interval flexibly with additional costs. In this paper, we study an unrelated parallel machine scheduling problem with machine- and sequence-dependent setup times and a special case of CPTs without extra costs. The objective is to maximize the difference between the sum of realized state of processing of all jobs and makespan. To solve the problem, a mixed integer programming (MIP) model is formulated first and then a logic-based Benders decomposition (LBBD) method is developed, in which the master problem is for job assignments and the subproblem is furthered decomposed into a sequencing problem for minimum total setup times on each machine and a processing time determination problem. Several LBBD-based heuristics are also employed by imposing different optimality gaps for the master problem. The performance of the MIP formulation, the exact LBBD method and the LBBD-based heuristics is compared through extensive computational experiments. The results demonstrate that the exact LBBD method with the preprocessing procedure which generates initial feasible solutions and cuts is effective and the proposed LBBD-based heuristics reduce the computation time significantly at the expense of slightly solution quality reduction.

Sowing rate and its effects on forage yield of tetraploid ryegrass

There is a shortage of information about the ryegrass crop (Lolium multiflorum Lam.), especially regarding the suitable sowing rate. Thus, the present work aimed to determine the most adequate sowing rate for tetraploid ryegrass cultivars. A tetraploid ryegrass population was sown at different densities: 150, 300, 600, 900, 1200, 1500, 1800 seeds/m². The number of plants per m², percentage of soil cover, leaf yield and green and dry forage yield were evaluated. The experimental design was randomized blocks with three replications. To observe the behavior of the pasture at different densities for each cut, regression analysis was performed, through which it was possible to verify that the sowing rate has greater influence on the initial cut of the crop. In all the variables analyzed by regression, only the second cut presented a linear trend favorable to the increase in density. In the other cuts, an increase was observed, both in the height of plants and in the yield variables, up to the density of 1500 seeds/m², with a subsequent fall to the highest density, indicating that higher densities may be detrimental to pasture yield. Therefore the density of 1500 seeds/m² is the most suitable for tetraploid ryegrass cultivars.

Looking into the Reservoir: Performance Evaluation of Fractured Long Horizontal Wells Using of Borehole Imaging Logs

Field G is a highly fractured and faulty field, this paper is seeking about the necessity to keep running Image logs in new oil wells and how the interpretation of the results would led the team to completing wells optimally and to design our well completion properly to prevent high initial water cut. Learnings are summarized from 40+ image logs ran in this field over the last few years. A cross field G seismic interpretation confirmed on lapping reservoirs and 3 major fault trends with different transmissibility. Also, sseismic and sub seismic Faults and fractures are confirmed from BHI with a NE-SW strike of field G and can be possibly related to production behavior of some wells. In 2015, field G Water Encroachment Study was conducted to identify the cause of high initial water cut of producers. It proposed that detecting fractures early via under-balanced drilling, Borehole Imaging Tools (BHI) and sealing the conduits with production packers would help reduce initial water-cuts [2]. BHI tools are open hole tools that measure either electrical conductivity of the borehole wall or the sonic travel time and amplitude. Micro-conductivity or amplitude and travel time measurements generate an image that shows bedding, fractures and many other fine-scale features. Acoustic tools are preferred in Oil Based Mud (OBM) system and hence they have not been used in field G to the extent that it required a dedicated discussion.

Pericardial and pulmonary actinomycosis, simulating inflammatory myofibroblastic tumor: the role of surgery

Background: Pericardial and pulmonary actinomycosis is a rare disease that remains undiagnosed during life due to a lack of clinical manifestations and a low positive culture rate. Actinomycosis can involve any part of the body. Thoracic actinomycosis is the second most common site after the cervicofacial. Patients with pulmonary actinomycosis usually present with a history of chest pain, cough, fever, shortness of breath on exertion, and sometimes massive hemoptysis. Pericardial involvement has been reported in the medical literature. It is written in line with process case series criteria. Method: From 2008 to 2021, 8 patients, 6 men, and 2 women (mean age 59 y) underwent surgical resection for thoracic lesion initially diagnosed as myofibroblastic tumor on true cut biopsy, but the final histopathologic report revealed actinomycosis. We reviewed preoperative clinical manifestations. Computed tomographic (CT) findings, preoperative true-cut biopsy report, surgical indications, and outcomes. Results: Five patients (62.5%) had poor oral hygiene; 2 patients (25%) had sinusitis, and 1 patient had bronchiectasis (12.5%). Seven patients were symptomatic (87.5%), with hemoptysis, shortness of breath, and weakness. One patient, 12.5%, presented with chest wall mass, chest pain, and fever. The basis of the imaging study (CT thorax). Six patients (87.5%) had CT guided biopsy that revealed a myofibroblastic tumor. In 2 patients (25%), CT scans showed the mass was close to the heart, so a biopsy was not done. We panned a surgical procedure based on the history of hemoptysis and a true cut-biopsy report. Four patients (50%) had a lobectomy, 2 patients (25%) had pericardial resection with a wedge of lung tissues, and 1 patient had chest wall resection enblock with right upper lobectomy. Conclusion: In patients with radiographic findings of pulmonary neoplasm and initial true cut biopsy report showing myofibroblastic tumor, surgery is mandatory. The final histopathology report showed actinomycoses. If the preoperative histopathologic diagnosis is available, then surgery has no role. The ideal treatment is the administration of systemic penicillin therapy. All our patients postoperatively received systemic antimicrobial therapy; they fully recovered and resumed back to everyday life.