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The surface science and engineering discipline has emerged recently and become more high‐profile. Functional performance of the surface is given top priority, although some of the bulk parameters play a very important role in the performance of the surface. Residual ductility is one such parameter, which directly controls the probability of surface embrittlement during the service stage of any engineering product, thereby controlling the embrittlement‐induced galvanic corrosion. Residual ductility also indirectly controls the metal dissolution in a corrosive environment by improving the adhesion of the corrosion product films to the surface. Discusses the role of residual ductility, in the control of environmentally induced deterioration of the metallic surfaces, highlighting the parameters which may eventually interfere with its level on the surface. Improvement of ductility also improves the attachment of the nearest neighbour elements of the matrix, resulting in the improvement of the surface stability. On the contrary, a brittle surface undergoes higher reactive interaction with the environment. Also discusses the possibility of using the residual ductility parameter for obtaining the rate values of an imaginary defect for subsequent extrapolation of the approximate residual life values of some carbon‐steel materials.

The purpose of this paper is to examine residual value risk modelling issues with a focus on automotive lease portfolios. Residual value risk is approached through a re‐sampling technique that provides the probability density function of losses and VaR measures for credit portfolios.

The methodology is applied to a portfolio of 37,523 operating leases issued between 1989 and 2001 by a major European financial institution.

The results show that residual value losses are low and sometimes non‐existent. Moreover, the major part of residual value risk is idiosyncratic and can thus be eliminated through adequate diversification. Additionally, this internal model seems to prove that capital requirements stemming from the Basel Committee's proposed new framework are somehow overestimated.

This paper advocates determining a more accurate risk weight for residual value risk in order to better reflect this relatively low‐risk part of leasing activities.

The purpose of this paper is to predict residual stresses in resistance spot weld of 2 mm thick aluminum 6061-T6 sheets. The joint use of finite element analysis and artificial neural networks can eliminate the high costs of residual stresses measuring tests and significantly shorten the time it takes to arrive at a solution.

Finite element method and artificial neural network have been used to predict the residual stresses. Different spot welding parameters such as the welding current, the welding time and the electrode force have been used for the simulation purposes in a thermal-electrical-structural coupled finite element model. To validate the numerical results, a series of experiments have been performed, and residual stresses have been measured. The results obtained from the finite element analysis have been used to build up a back-propagation artificial neural network model for residual stresses prediction.

The results revealed that the neural network model created in this study can accurately predict residual stresses produced in resistance spot weld. Using a combination of these two developed models, the residual stresses can be predicted in terms of spot weld parameters with high speed and accuracy.

The paper includes implication for aircraft and automobile industries to predict residual stresses. Residual stresses can lower the strength and fatigue life of the spot-welded joints and determine the performance quality of the structure.

This paper presents an approach to reduce the high costs and long times of residual stresses measuring tests.

Assume that we generate forecasts from a model y=cx+d+ξ. The constants “c” and “d” are placement parameters estimated from observations on x and y, and ξ is the residual error variable.

Our objective is to develop a method for accurately measuring and evaluating the risk profile of a forecasted variable y. To do so, it is necessary to first obtain an accurate representation of the histogram of a forecasting model's residual errors. That is not always so easy because the histogram of the residual ξ may be symmetric, or it may be skewed to either the left of or to the right of its mode. We introduce the probability density function (PDF) family of functions because it is versatile enough to fit any residual's locus be it skewed to the left, symmetric about the mean, or skewed to the right. When we have measured the residual's density, we show how to correctly calculate the risk profile of the forecasted variable y from the density of the residual using the PPD function. We achieve the desired and accurate risk profile for y that we seek. We conclude the chapter by discussing how a universally followed paradigm leads to misstating the risk profile and to wrongheaded decisions by too freely using the symmetric Gauss–normal function instead of the PPD function. We expect that this chapter will open up many new avenues of progress for econometricians.

This article aims to investigate and model the effects of welding-generated thermal cycle on the resulting residual stress distribution and its role in the initiation and propagation of fatigue failure in thick shaft sections.

Experimental and numerical techniques were applied in the present study to explore the relationship(s) between welding residual-stress distribution and fatigue failure characteristics in a hydropower generator shaft. Experimental techniques included stereomicroscopy, optical and scanning electron microscopy (SEM), chemical analysis and mechanical testing. Finite element modelling (FEM) was used to model the shaft welding cycle in terms of thermal (temperature) history and the associated development of residual stresses within the weld joint.

Experimental analyses have confirmed the suitability of the used material for the intended application and confirmed the failure mode to be low cycle fatigue. The observed failure characteristics, however, did not match with the applied loading in terms of design stress levels, directionality and expected crack imitation site(s). FEM results have revealed the presence of a sharp stress peak in excess of 630 MPa (about 74% of material's yield strength) around weld start point and a non-uniform residual stress distribution in both the circumferential and through-thickness directions. The present results have shown very close matching between FEM results and observed failure characteristics.

The present article considers an actual industrial case of a hydropower generator shaft failure. Present results are valuable in providing insight information regarding such failures as well as some preventive design and fabrication measures for the hydropower and other power generation and transmission sector.

The presence of the aforementioned stress peak around welding start/end location and the non-uniform distribution of residual-stress field are in contrast to almost all published results based on some uniformity assumptions. The present FEM results were, however, the only stress distribution scenario capable of explaining the failure considered in the present research.

The purpose is to predict the distribution of the residual pretightening force of the bolt group under the action of any initial pretightening force, and to achieve the final residual pretightening force as the target to solve the initial pretightening force value to be applied.

Based on the finite element method and the elastic interaction theory between bolt group, this paper establishes a prediction model for the residual pretightening force distribution of bolt group for one-step pretightening and multi-step pretightening of gasketless flange connection systems. In addition, using the general modeling method given in this paper, the prediction model of residual pretightening force of long plate bolt connection system is established, and compared with reference, which fully proves the effectiveness and universality of the general prediction model of residual pretightening force of bolt group.

The appropriate pretightening sequence, increasing the number of pretightening steps and variable amplitude loading can effectively reduce the influence of elastic interaction and improve the uniformity of residual pretightening force of the bolt group. And the selection of material, number of bolts and connected thickness of bolt connection system also has a great influence on the distribution of residual pretightening force of bolt groups.

The general prediction model for the residual pretightening force of bolt group of connecting structural components considering elastic interaction given in this paper can provide a reference for the design and optimization of the bolt assembly process of the rotor system and the casing system in aero-engine and the prediction of the performance of the connecting system.

Since columns are critical structural elements, they shall withstand hazards without any considerable damage. In the case of a fire, although concrete has low thermal conductivity compared to other construction materials, its properties are changed at elevated temperatures. Most critically, the residual compressive strengths of reinforced concrete columns are significantly reduced after fire exposure. Validation of the worthiness of rehabilitating concrete structures after fire exposure is highly dependent on accurately determining the residual strengths of fire-damaged essential structural elements such as columns.

In this study, eight reinforced-concrete columns (200 × 200 × 1,500 mm) that were experimentally examined in a prior related study have been numerically modelled using ABAQUS software to investigate their residual compressive strengths after exposure to different durations of standard fire (i.e. one and two hours) while subjected to different applied load ratios (i.e. 20 and 40% of the compressive resistance of the column). Outcomes of the numerical simulations were verified against the prior study's experimental results.

In a subsequent phase, the results of a parametric study that has been completed as part of the current study to investigate the effects of the applied load ratios show that the application of axial load up to 80% of the compressive resistance of the column did not considerably influence the residual compressive strength of the shorter columns (i.e. 1,500 and 2,000-mm high). However, increasing the height of the column to 2,500 or 3,000 mm considerably reduced the residual compressive strength when the load ratio applied on the columns exceeded 60 and 40%, respectively. Also, when the different columns were simulated under two-hour standard fire exposure, the dominant failure was buckling rather than concrete crushing which was the typical failure mode in most columns.

The outcomes of the numerical study presented in this paper reflect the residual compressive strength of RC columns subjected to various applied load ratios and standard fire durations. Also, the parametric study conducted as part of this research on the effects of higher load ratios and greater column heights on the residual compressive strength of the fire-damaged columns is practical and efficient. The developed computer models can be beneficial to assist engineers in assessing the validity of rehabilitating concrete structures after being exposed to fire.

Laser-based powder bed fusion (LPBF) is a new method for forming thin-walled parts, but large cooling rates and temperature gradients can lead to large residual stresses and deformations in the part. This study aims to reduce the residual stress and deformation of thin-walled parts by a specific laser rescanning strategy.

A three-dimensional transient finite element model is established to numerically simulate the LPBF forming process of multilayer and multitrack thin-walled parts. By changing the defocus amount, the laser in situ annealing process is designed, and the optimal rescanning parameters are obtained, which are verified by experiments.

The results show that the annealing effect is related to the average surface temperature and scan time. When the laser power is 30 W and the scanning speed is 20 mm/s, the overall residual stress and deformation of the thin-walled parts are the smallest, and the in situ annealing effect is the best. When the annealing frequency is reduced to once every three layers, the total annealing time can be reduced by more than 60%.

The research results can help better understand the influence mechanism of laser in situ annealing process on residual stress and deformation in LPBF and provide guidance for reducing residual stress and deformation of LPBF thin-walled parts.

Taking a mental accounting theory perspective, this study explores how pricing strategy (all-inclusive vs partitioned) influences consumers' perceived residual value of a product and their subsequent intentions to upgrade to a newer model.

A pilot study and two formal experiments were conducted to test the hypotheses.

A partitioned (vs all-inclusive) price causes consumers to later recall a lower total cost and perceive lower residual value for the existing product, thereby increasing upgrade intentions. This finding holds for both utilitarian and hedonic products. Perceived residual value mediates the impact of the pricing strategy on upgrade intentions. The pricing strategy effect is stronger for state-oriented individuals than for action-oriented individuals.

This study extends understanding of the impact of pricing strategies from consumers' short-term immediate demand to long-term upgrade intentions. It also identifies a previously uninvestigated moderator (action-state orientation), clarifying the boundary conditions of pricing strategy effects. The study's conceptual framework links pricing strategy, sunk costs, perceived residual value and upgrade intentions, providing rich insights and potential research paths. These findings further enhance understanding of upgrade intentions.