Safe Domains Research Articles

Investigating Optimum Hot Working Window of 2205 Duplex Stainless Steel Using Modified Dynamic Material Modeling

AbstractThis paper uses a modified dynamic material modeling (MDMM) suggested by Murty and Rao to develop processing maps (PM) of 2205 duplex stainless steels (DSS). Gleeble 1500D, a thermo-mechanical simulator was used to conduct single hit compression tests at a temperature between 850 and 1050 °C and strain rates of 0.001-5 s−1. Additionally hot compression tests at a strain rate of 15 s−1 and same temperature range were also conducted on a Bahr 805 dilatometer. As per general procedure acquired stress-strain data were corrected for friction and adiabatic heating, before constructing PMs at true strains of 0.1, 0.3, 0.5 and 0.8. Microstructures to validate the PM were prepared from safe domains and instability regimes belonging to PM of 0.8 true strain. Results showed that hot processing at intermediate to high strain rates and temperature leads to formation of flow instabilities such as mechanical twins and adiabatic shear bands. Safe domain located within the temperature range of (850-925) °C, strain rates of (2.6-15) s−1 and peak η = 35% gave an inhomogeneous microstructure with presumably non-uniform mechanical properties. This region was considered ideal for hot processing of 2205 DSS provided that deformation conditions are carefully controlled to optimise DRX. Low Z conditions also provided an optimum hot working for hot processing.

An Investigation on unstable flow during hot deformation of Inconel X750 superalloy using 3D processing map and shear band formation criterion

In this study, deformation efficiency and instability criteria were employed to delineate the unstable flow regions for Inconel X750 superalloy through high temperature deformation. High temperature stress–strain data attained from isothermal hot compression experiments in the temperature range of 950–1150 °C and strain rates between 0.0001 and 1 s⁻¹ to identify safe and un-safe deformation domains in terms of an integrated 3D processing maps. These domains were validated through detailed microstructure observation and material tendency to shear band formation in terms of the competition between work hardening and strain rate sensitivity i.e. flow localization parameter. The superimposed effect of microstructure features like dynamic precipitation, dynamic recovery (DRV), and dynamic recrystallization (DRX) with destructive shear banding were responsible for controlling the material behaviour. Based on the TEM images, it was observed that material revealed stable flow at lower strain rates while adiabatic shear band and flow localization occurred at higher strain rates due to activation of slip systems and cell formation.

Prevention of brittle failure for steel connections utilizing special devices

The present paper proposes the use of a special design procedure devoted to the prevention of brittle failure for welded steel connections. In particular, reference is made to steel frame structures made up of beam elements with I-shaped cross-sections where the connections between columns and beams are usually welded and/or bolted. The proposed new design procedure consists of four subsequent analysis steps; it is based on the identification and analytical definition of new appropriate brittle safe domains defined in the N,V,M space and on the use of suitably designed devices (LRPD), recently proposed by the authors, belonging to the class of the RBS connections. The latter are able to impose prefixed values of internal forces on selected beam element cross-sections, avoiding any modification of the elastic stiffness features of the involved beam. The main novelties of the present study consist in the introduction of new brittle safe domains for I-shaped cross-sections, in the specialization of the LRPD optimal design to the present context and in the definition of a special design strategy which allows to contextually obtain structures safe from the risk of brittle failure as well as being able to dissipate an appropriate amount of plastic strain energy. The numerical application, devoted to plane steel frames, confirms the sound reliability of the procedure and the great flexibility of the utilized LRPDs.

Comparing the Cold, Warm, and Hot Deformation Flow Behavior of Selective Laser‐Melted and Electron‐Beam‐Melted Ti–6Al–2Sn–4Zr–2Mo Alloy

The cold, warm, and hot deformation flow behavior and mechanical properties of the Ti‐6242 alloy produced by selective laser melting (SLM) and electron beam melting (EBM) are compared. Hot compression tests are conducted over a wide temperature range (100–1000 °C) at a constant strain rate of 0.001 s−1. The yield and overall strength levels of the SLMed specimens are higher than those of the EBMed specimens at all temperatures. A thermally stable region is observed for SLMed specimens in the temperature range of 100–700 °C, but the strength level drops significantly (approximately 300–500 MPa) at above 700 °C. The stability region shifts to the lower temperature range of 100–600°Cfor the EBMed specimens, and strength starts to decrease at 600 °C. Both specimens experience fracture in a cold‐temperature regime but exhibit a high strain tolerance of approximately 0.4. The SLMed samples display a completely brittle behavior at a warm temperature regime, whereas, the EBMed specimens demonstrate better formability, tolerating higher compressive strains. The softening fraction substantially increases at high temperatures, indicating safe domains for thermomechanical processing of additively manufactured Ti6242 alloy.

Reinforcement Learning-Based Decentralized Safety Control for Constrained Interconnected Nonlinear Safety-Critical Systems.

This paper addresses the problem of decentralized safety control (DSC) of constrained interconnected nonlinear safety-critical systems under reinforcement learning strategies, where asymmetric input constraints and security constraints are considered. To begin with, improved performance functions associated with the actuator estimates for each auxiliary subsystem are constructed. Then, the decentralized control problem with security constraints and asymmetric input constraints is transformed into an equivalent decentralized control problem with asymmetric input constraints using the barrier function. This approach ensures that safety-critical systems operate and learn optimal DSC policies within their safe global domains. Then, the optimal control strategy is shown to ensure that the entire system is uniformly ultimately bounded (UUB). In addition, all signals in the closed-loop auxiliary subsystem, based on Lyapunov theory, are uniformly ultimately bounded, and the effectiveness of the designed method is verified by practical simulation.

Failure probability estimation and detection of failure surfaces via adaptive sequential decomposition of the design domain

We propose an algorithm for selection of points from the design domain of small to moderate dimension and for failure probability estimation. The proposed active learning detects failure events and progressively refines the boundary between safe and failure domains thereby improving the failure probability estimation. The method is particularly useful when each evaluation of the performance function g(x) is very expensive and the function can be characterized as either highly nonlinear, noisy, or even discrete-state (e.g., binary). In such cases, only a limited number of calls is feasible, and gradients of g(x) cannot be used. The input design domain is progressively segmented by expanding and adaptively refining a mesh-like lock-free geometrical structure. The proposed triangulation-based approach effectively combines the features of simulation and approximation methods. The algorithm performs two independent tasks: (i) the estimation of probabilities through an ingenious combination of deterministic cubature rules and the application of the divergence theorem and (ii) the sequential extension of the experimental design with new points. The sequential selection of points from the design domain for future evaluation of g(x) is carried out through a new decision approach, which maximizes instantaneous information gain in terms of the probability classification that corresponds to the local region. The extension may be halted at any time, e.g., when sufficiently accurate estimations are obtained. Due to the use of the exact geometric representation in the input domain, the algorithm is most effective for problems of a low dimension, not exceeding eight. The method can handle random vectors with correlated non-Gaussian marginals. When the values of the performance function are valid and credible, the estimation accuracy can be improved by employing a smooth surrogate model based on the evaluated set of points. Finally, we define new factors of global sensitivity to failure based on the entire failure surface weighted by the density of the input random vector.

Nonlinear dynamics and safety aspects of pressure relief valves

Direct spring operated pressure relief valves are regular elements of high-pressure hydraulic systems; however, valve vibrations may still occur endangering the valve and the protected system. The damping of these vibrations is a crucial issue, whereas the external viscous damping at the valve cannot be increased boundlessly based on safety aspects. The vibrations emerge via Hopf bifurcations of either super- or subcritical type, and the nonlinear characteristics have an important role in the valve dynamics. Thorough nonlinear analysis is needed to guarantee safe operation. The linear stability analysis is extended by local and global bifurcation analysis to reveal the stable domains bounded by subcritical Hopf points and the possible bistabilities that exclude the safe operation. Afterwards, the effect of a downstream pipe is analysed, which can also carry safety risks based on the literature; however, the time delay originated in the wave propagation in the pipe may also have stabilising effects. The nonlinear analysis of the presented system compares analytical, semi-analytical and numerical results and assigns the safe parameter domains of the valve with respect to a wide range of relevant parameter variations.

Novel design procedure for steel hysteretic dampers in seismic retrofit of frame structures

An energy-based design procedure for sizing dissipative bracing systems equipped with steel hysteretic dampers is proposed for application to the seismic retrofit of frame structures. The procedure is based on the following assumptions: it is not iterative, as it provides a direct estimation of the steel dissipater sizes; the stiffening effects of dampers reduce displacements below prefixed limits; their damping effects reduce displacements and stress states to keep the response of structural members within their safe domains up to medium-to-high levels of the input seismic action. The procedure is articulated in three steps: seismic assessment analysis in current state and definition of the elastic properties of the bracing system to be installed in the structure; design of the dampers; verification of the seismic performance of the structure in retrofitted conditions. A demonstrative case study concerning a precast reinforced concrete frame school building is offered to explicate the practical application of the procedure, as well as to evaluate the enhancement of its response generated by the intervention. The latter consists in incorporating a dissipative bracing system equipped with triangular-shaped added damping and stiffness (T-ADAS) steel hysteretic devices. The two limit hypotheses assumed in the computational analyses for the roof beam-to-column connections of the building, i.e. hinges or fixed-ends, allow to discuss how the fundamental period of the structure in current conditions affects the parameters involved in the sizing process of the T-ADAS dampers.

Hot deformation constitutive analysis and processing maps of the as-cast and wrought Mg–2.5Gd–0.5Zr alloy

Hot deformation behavior and constitutive analysis of the as-cast and extruded Mg–2.5Gd–0.5Zr alloy were compared, using the shear punch testing (SPT) method in the temperature range of 623–723 K and shear strain rate range of 2.8 × 10–3–2.2 × 10–2 s–1. The respective hyperbolic-sine exponents of 2.67 and 2.59 as well as activation energies of 183 and 275 kJ mol–1 obtained for the as-cast and extruded alloy suggested grain boundary sliding as the prevailing deformation mechanism. Surprisingly, regardless of the instability domains, the efficiency of power dissipation exceeded 30% in most areas in the processing maps of both cast and wrought conditions. The safe and instability domains were rather similar in both processing maps. The relatively high potential of the as-cast alloy for hot deformation, despite its initial coarse grain size of about 150 µm, can be ascribed to the severe dynamic recrystallization (DRX) during hot deformation caused by Zr. This could be economically advantageous, as there would be no need for homogenization of the as-cast material before deformation processing. The most noticeable optimum window occurred in the temperature range of 673–723 K for both as-cast and extruded conditions with a vaster strain-rate range for the extruded one (5.6 × 10–3–1.4 × 10–2 s–1), owing to its initial finer grain size. The instability domains, however, took place for both conditions in the temperature range of 648–673 K and strain rates of about 5.6 × 10–3 s–1, manifested by cracking in the deformed zone, and also at temperatures higher than 673 K and medium to high strain rates.

Effect of nearby strip loading on lateral capacity of offshore large-diameter monopiles in clay slope

This study is devoted to investigating the effect of nearby strip loading on the lateral bearing capacity of offshore large-diameter monopiles at the crest of marine clay slope by the finite element limit analysis (FELA) method. After the successive validations by cases of rigid piles and strip footings at the clay slope crest, the safe domains for the laterally loaded large-diameter monopiles are defined by the failure envelopes relating the dimensionless lateral bearing capacity H u/(c u D 2) to dimensionless strip loading q/c u. Particularly, all failure envelopes are depicted by closed-form expressions and design charts can then be given for a quick and straightforward assessment of dimensionless lateral bearing capacity for a wide range of frequently-encountered cases. In addition, the interaction between the pile bearing capacity and nearby strip loading is characterized by introducing the relationship of normalized parameters H u/(c u D 2) and q/c u, then graphically explained by plastic multiplier contour plots. Several kinds of representative curves are given successively to further clarify the effects of dimensionless factors on the interaction.

Hot-Deformation Behavior and Processing Maps of a Low-Carbon Fe-2 wt% Nb Steel

In the present work, the deformation behavior and processing maps of a low-carbon Fe-2 wt% Nb steel were studied by means of hot-compression tests at temperatures of 800–1150 °C and strain rates of 0.01–10 s−1. The hot-processing maps at different strains and corresponding microstructural evolution were constructed and discussed. The hot-deformation behaviors of two different phase regions, i.e., austenite + NbC dual-phase and ferrite + NbC dual-phase, were predicted by determining the constitutive equations using Arrhenius-type and Zener–Hollomon models. The results suggest that the hot-deformed microstructures of the material present a strong correlation with the processing parameters in the hot-processing maps. In addition, the optimum parameters based on the processing maps were obtained, and the instable and the safe domains during the hot deformation in the hot-processing maps provide solid theoretical guidance for industrial production.

Safety and Risk Analysis of Autonomous Vehicles Using Computer Vision and Neural Networks

The autonomous vehicle (AVs) market is expanding at a rapid pace due to the advancement of information, communication, and sensor technology applications, offering a broad range of opportunities in terms of energy efficiency and addressing climate change concerns and safety. With regard to this last point, the rate of reduction in accidents is considerable when switching safety control tasks to machines from humans, which can be noted as having significantly slower response rates. This paper explores this thematic by focusing on the safety of AVs by thorough analysis of previously collected AV crash statistics and further discusses possible solutions for achieving increased autonomous vehicle safety. To achieve this, this technical paper develops a dynamic run-time safe assessment system, using the standard autonomous drive system (ADS), which is developed and simulated in case studies further in the paper. OpenCV methods for lane detection are developed and applied as robust control frameworks, which introduces the factor of vehicle crash predictability for the ego vehicle. The developed system is made to predict possible crashes by using a combination of machine learning and neural network methods, providing useful information for response mechanisms in risk scenarios. In addition, this paper explores the operational design domain (ODD) of the AV’s system and provides possible solutions to extend the domain in order to render vehicle operationality, even in safe mode. Additionally, three case studies are explored to supplement a discussion on the implementation of algorithms aimed at increasing curved lane detection ability and introducing trajectory predictability of neighbouring vehicles for an ego vehicle, resulting in lower collisions and increasing the safety of the AV overall. This paper thus explores the technical development of autonomous vehicles and is aimed at researchers and practitioners engaging in the conceptualisation, design, and implementation of safer AV systems focusing on lane detection and expanding AV safe state domains and vehicle trajectory predictability.

Hot working behaviour and processing maps of duplex cast steel

Abstract In this paper the hot working behaviour of medium carbon duplex cast steel is studied using uniaxial hot compression tests over a temperature range varying from 700 ˚C to 1 000 °C and at different strain rates ranging from 10–4 to 10–1 s–1. A model based on a variant of a dynamic materials model was employed to construct processing maps. These maps delineate the safe and unsafe domains. The safe domains, associated with dynamic recrystallization and dynamic recovery, can be chosen to optimize the hot workability of the studied material. Whereas, the unsafe domain is to be avoided because it is associated with plastic deformation instabilities. The domain associated with dynamic recrystallization is centred at 1000 °C and 10–4 s–1 with a peak energy dissipation efficiency of about 40%, while the domain associated with dynamic recovery is centred at 700 °C and 10–4 s–1 with a peak energy dissipation efficiency of about 27%. The unsafe hot working domain, spread over the entire temperature range and moderate to high strain rates, predicts the appearance of flow instabilities, in the form of shear bands and intergranular cracks. To validate the obtained results, microstructural observations corresponding to different processing conditions are presented.

Prediction of thermo-mechanical behavior and microstructural evolution of copper considering initial grain size at elevated temperature

To characterize and evaluate the workability of pure copper, the hot compression test at temperature range of 673–1073 K, strain rate range of 0.001–0.1s−1 and two initial grain sizes (IGS) of 20 and 50μm with 60% deformation were performed. The results of the true stress-strain curve showed that the processing parameters including IGS, temperature, strain rate, and strain have a significant effect on the elevated temperature behavior of pure copper. As the flow curve of finer grain size at lower temperatures has higher flow stress than the larger grain size which is reversed by increasing the temperature due to changes in the deformations mechanism. A hyperbolic-sine Arrhenius model and strain-compensated Arrhenius constitutive equation with good accuracy were developed to describe and predict the hot flow behavior of this material. The activation energy was determined in different processing conditions for two different IGS and the results showed that this energy increases with increasing strain, and its values are greater for finer grain sizes. The investigation of the deformation mechanism showed that the mechanism of cross-slip and dislocation climb controlled the deformation process are dominant mechanisms for IGS of 20μm whereas self-diffusion is the dominant mechanism for IGS of 50μm. To determine the safe and optimal conditions for hot deformation, the processing maps were drawn based on DMM theory at different strains. Finally, by examining and evaluating the microstructure under different processing conditions, the dominant mechanisms were identified for the two investigated IGS at different temperature ranges and strain rates, and the safe and unsafe domains were specified for the hot deformation of copper.

Introdução a métodos de ensino introduction to teaching methods introducción a los métodos de enseñanza

Teaching methods are proposed, classified and described by the Methodology discipline, however it is up to Didactics to judge or criticize these teaching methods. A method consists of a disciplined, orderly and calculated way of proceeding to achieve a desired goal. Based on these constitutive elements, the didactic method is the rational and practical organization of the educator's resources and procedures, aiming to lead the students' learning to the expected and desired results. In other words, the didactic method intends to take the students to the safe and satisfactory domains of the subject, expanding their knowledge, enriching their experience and developing their capacity, making them more apt for life in society and more qualified for their future professional work.

VITALITAS BAHASA JAWA DAN BAHASA MADURA DI DESA REJOYOSO, KECAMATAN BANTUR, KABUPATEN MALANG (KAJIAN SOSIOLINGUISTIK)

Rejoyoso Village is a village with two ethnicities, namely Javanese and Madura. Rejoyoso village was chosen as a research area by reason of the existence of bilingualism in 70% of the community. Bilingualism in question is the mastery of two regional languages as the first language and second language (Javanese and Madura). Javanese is dominant in the hamlets of Wotgalih and Balong. Madurese language is dominant in Sukosari and Karangsuko Hamlets. This research focuses on the domains which influence communication and the vitality of Javanese and Madurese languages in Rejoyoso. This research is a quantitative descriptive study using a questionnaire instrument. The research location is in Rejoyoso Village by taking samples from hamlets in Rejoyoso in accordance with the dominance of the language. The results of this study indicate that the vitality of Javanese and Madurese languages is not on a safe scale, but on a vulnerable scale (stable and stable, but endangered). The use of regional languages is low in domains such as population mobility, governance, education, transactions, bilingualism, poverty, language attitudes, and religion. The safe domains are the family domain, the neighborhood and the domain of expression.

Binary classification method for efficient and accurate system reliability analyses of layered soil slopes

ABSTRACT To enhance the computational efficiency in slope reliability analyses, a binary classification method (BCM) that takes advantage of a judgement-based strength reduction method (SRM) and an active-learning support vector machine (SVM) was developed to conduct system reliability analyses of layered soil slopes. The SVM was naturally employed to establish a binary classifier via the judgment technique to approximate the true limit state function because the stability state (e.g. stable or unstable) of a slope can be determined without calculating its exact factor of safety according to the SRM. An active-learning technique was developed to iteratively search training samples in the vicinity of the border between safe and failure domains, to update the SVM classifier with the aid of a modified initial sampling rule. Then, Latin hypercube sampling was employed, together with the obtained SVM classifier, to compute the slope system probability of failure. Three representative examples taken from the literature were employed to evaluate the performance of the proposed method. The proposed BCM shows great computational efficiency compared with existing methods. It reduced the computational cost to several minutes for simple slopes and to approximately 30 minutes for a complex real case, while maintaining a good computational accuracy.

Construction of hot deformation processing maps for 9Cr-1Mo steel through conventional and ANN approach

The behavior of hot deformed flow curves in a 9Cr-1Mo steel have been analysed using constitutive and artificial neural network (ANN) approaches. At each temperature (850 ° C-1100 ° C) various strain rates (0.001 s−1–10 s−1) of deformation behavior has been analysed. The corrections of flow stress due to the adiabatic temperature rise during hot deformation have been made through artificial neural network (ANN) method and compared it with the linear interpolation (conventional) method. The temperature corrected (conventional) flow stress has been compared and analyzed with the predicted flow stress data obtained by established constitutive equation. Additionally, the experimental flow stresses obtained by thermomechanical simulator have also been compared and analyzed with predicted flow stresses obtained by ANN method. Further, the predicted and corrected flow stress curves obtained by ANN method have been compared and analyzed. The processing maps at 0.6 true strain based on flow stress data corrected through both ANN and conventional methods have been compared. Upon analyzing the safe and unsafe domains of the maps with the corresponding microstructures, the ANN approach depicted the best precise results over that of the conventional method. Variation in strain hardening rate and correlated it with EBSD analysis have also been carried out to analyze the variation in hardness for some of the deformed specimens.

Classifying Drugs by their Arrhythmogenic Risk Using Machine Learning

All medications have adverse effects. Among the most serious of these are cardiac arrhythmias. Current paradigms for drug safety evaluation are costly, lengthy, conservative, and impede efficient drug development. Here, we combine multiscale experiment and simulation, high-performance computing, and machine learning to create a risk estimator to stratify new and existing drugs according to their proarrhythmic potential. We capitalize on recent developments in machine learning and integrate information across 10 orders of magnitude in space and time to provide a holistic picture of the effects of drugs, either individually or in combination with other drugs. We show, both experimentally and computationally, that drug-induced arrhythmias are dominated by the interplay between two currents with opposing effects: the rapid delayed rectifier potassium current and the L-type calcium current. Using Gaussian process classification, we create a classifier that stratifies drugs into safe and arrhythmic domains for any combinations of these two currents. We demonstrate that our classifier correctly identifies the risk categories of 22 common drugs exclusively on the basis of their concentrations at 50% current block. Our new risk assessment tool explains under which conditions blocking the L-type calcium current can delay or even entirely suppress arrhythmogenic events. Using machine learning in drug safety evaluation can provide a more accurate and comprehensive mechanistic assessment of the proarrhythmic potential of new drugs. Our study paves the way toward establishing science-based criteria to accelerate drug development, design safer drugs, and reduce heart rhythm disorders.

Optimal Plastic Analysis of Structures under Uncertain Conditions

In this study optimum plastic shakedown analysis of framed steel structures with semi-rigid connections (SRC) between beam and columns subjected to multi-parameter static loading presented. Since shakedown analysis does not provide information concerned with the accumulated residual displacements, complementary strain energy of the residual force (CSERF) considered as constrain to evaluate the post yield behavior of framed steel structures. The constraints on the CSERF are modelled using probabilistic and deterministic methods. To evaluate the maximum shakedown load-multipliers a numerical example is introduced, shakedown load-multipliers are calculated and safe loading domains of the framed steel structure are illustrated. The numerical results show that the constraints on CSERF, SRC and probabilistic given constraints can influence on the value of the shakedown load-multipliers.