A resilience-based approach in managing the closure and abandonment of large mine tailing ponds

Mining tailing ponds are large infrastructure objects whose life cycle spans over several decades.They are indispensable for certain types of mines where technological process produces and rejects mud.They also have potential to generate risks for human life,property and environment.For that reason,it is essential to adequately manage them throughout all the stages of their life cycle.The phase of their closure and abandonment is less studied and understood.The paper proposes a holistic resilience-based approach for analyzing this phase of their life cycle.The proposed methodology is validated through a case study at an actual surface iron ore mine in Bosnia and Herzegovina.

Microstructure,mechanical properties,and wear resistance of VCp-reinforced Fe-matrix composites treated by Q&P process

A quenching and partitioning(Q&P) process was applied to vanadium carbide particle(VCp)-reinforced Fe-matrix composites(VC-Fe-MCs) to obtain a multiphase microstructure comprising VC, V8 C7, M3 C, α-Fe, and γ-Fe. The effects of the austenitizing temperature and the quenching temperature on the microstructure, mechanical properties, and wear resistance of the VC-Fe-MCs were studied. The results show that the size of the carbide became coarse and that the shape of some particles began to transform from diffused graininess into a chrysanthemum-shaped structure with increasing austenitizing temperature. The microhardness decreased with increasing austenitizing temperature but substantially increased after wear testing compared with the microhardness before wear testing; the microhardness values improved by 20.0% ± 2.5%. Retained austenite enhanced the impact toughness and promoted the transformation-induced plasticity(TRIP) effect to improve wear resistance under certain load conditions.

Stress-corrosion behavior and characteristics of the friction stir welding of an AA2198-T34 alloy

To better understand the stress-corrosion behavior of friction stir welding(FSW),the effects of the microstructure on the stress-corrosion behavior of the FSW in a 2198-T34 aluminum alloy were investigated.The experimental results show that the low-angle grain boundary(LABs)of the stir zone(SZ)of FSW is significantly less than that of heated affected zone(HAZ),thermo-mechanically affected zone(TMAZ),and parent materials(PM),but the grain boundary precipitates(GBPs)T1(Al2CuLi)were less,which has a slight effect on the stress corrosion.The dislocation density in SZ was greater than that in other regions.The residual stress in SZ was+67 MPa,which is greater than that in the TMAZ.The residual stress in the HAZ and PM is-8 MPa and-32 MPa,respectively,and both compressive stresses.The corrosion potential in SZ is obviously less than that in other regions.However,micro-cracks were formed in the SZ at low strain rate,which indicates that the grain boundary characters and GBPs have no significant effect on the crack initiation in the stress-corrosion process of the AA2198-T34.Nevertheless,the residual tensile stress has significant effect on the crack initiation during the stress-corrosion process.

Influence of carbon-partitioning treatment on the microstructure, mechanical properties and wear resistance of in situ VCp-reinforced Fe-matrix composite

The wear resistance of iron(Fe)-matrix materials could be improved through the in situ formation of vanadium carbide particles(VCp)with high hardness.However,brittleness and low impact toughness limit their application in several industries due to addition of higher carbon content.Carbon-partitioning treatment plays an important role in tuning the microstructure and mechanical properties of in situ VCp-reinforced Fe-matrix composite.In this study,the influences of carbon-partitioning temperatures and times on the microstructure,mechanical properties,and wear resistance of in situ VCp-reinforced Fe-matrix composite were investigated.The experimental results indicated that a certain amount of retained austenite could be stabilized at room temperature through the carbon-partitioning treatment.Microhardness of in situ VCp-reinforced Fematrix composite under carbon-partitioning treatment could be decreased,but impact toughness was improved accordingly when wear resistance was enhanced.In addition,the enhancement of wear resistance could be attributed to transformation-induced plasticity(TRIP)effect,and phase transformation was caused fromγ-Fe(face-centered cubic structure,fcc)toα-Fe(body-centered cubic structure,bcc)under a certain load.

Thin Oxide Film Growth during Final Annealing of Stainless Steels

After the cold rolling sequence of the production line,stainless steels strips present highly disordered structure and have to be annealed to recover their crystalline structure.This operation takes place by passing the moving strip through a furnace heated by combustion of natural gas with little air excess.Although the time at high temperature is short(<1 min),the formed surface oxide is thick enough to modify the surface aspect of the steel,making necessary subsequent chemical pickling.The present work explores the oxidation step of various stainless steels during final annealing in order to better understand the mechanisms involved and make further improvements in the pickling sequence.

A roadmap to carbon-lean steel

The steel industry has come a long way in increasing its energy efficiency.In Europe the carbon intensity of steelmaking over the last 40 years was decreased by a factor 2.The potential for further improvements is now becoming less obvious as blast furnace operations are approaching the thermodynamical lower limit of hot metal production.To take on the climate change challenge and be able to respond to the expectation for strong reduction of carbon emissions,ArcelorMittal(AM) has developed a two step approach: (1) In a first instance given the modest remaining potential for incremental improvements precise benchmark tools were developed.This allowed identifying the top runners and determining the remaining potential for improvement.Plans were developed to bridge the gap with this achievable performance.In total a plan was devised with more than 400 identified actions throughout the group.This action plan will allow achieving a further 8% increase of CO_2 efficiency by 2020. (2 ) Secondly,already in 2002 AM engaged in the development of breakthrough technologies to further drastically reduce the carbon intensity of steelmaking.After screening a large number of candidates a few were selected for further development.A first breakthrough technology which is the most advanced stage of development can be applied to existing blast furnace and is reaching maturity and a demonstration on industrial scale of this technology is under preparation.In itself this technology will decrease the dependency on carbon as well as increase the productivity of the original blast furnaces.Real big gains can be made if this technology can be combined with underground carbon storage. In the AM roadmap the impact of raw materials(DRI,scrap) was excluded.In the longer run however the attention will have to turn to the overall footprint of materials and the long term consequences of the choice of materials.Increasing the recovery while preserving the quality of used steel products will leverage greatly the efforts done in the production of primary and secondary steel and power.

微合金低碳钢高温拉伸实验过程的有限元模拟

开发了电势-热-力耦合有限元计算模型,该模型考虑了微合金低碳钢高温条件下的奥氏体γ和高温铁素体δ相变,建立了多相混合力学模型,描述了(δ+γ)两相混合区的力学行为.应用多场耦合计算模型对拉伸实验过程进行了数值模拟.实验及数值模拟结果表明,拉伸试样内存在较大径向及轴向温度梯度,该温度梯度导致试样内产生相体积分数的梯度分布,如高温铁素体相分数和液相分数的梯度分布,试样内产生非均匀变形,并且应力分布极不均匀.在进行实验钢高温力学本构方程的参数标定时,采用名义应力—应变的方法会导致较大误差,而基于数值模拟的方法则是十分有效及准确的,如本文所建立的数值模型.

Effect of substitution of Si by Al on the microstructure and mechanical properties of bainitic transformation-induced plasticity steels

The effect of partial or full substitution of Si by Al on the microstructure and mechanical properties has been extensively studied in multi-phase transformation-induced plasticity（TRIP） steels with polygonal ferrite matrix, but rarely studied in bainitic TRIP steels. The aim of the present study is to properly investigate the effect of Al and Si on bainite transformation, microstructure and mechanical properties in bainitic steels in order to provide guidelines for the alloying design as a function of process parameters for the 3 rd generation advanced high strength steels（AHSS）. It is shown from the dilatometry study,microstructural investigations and tensile properties measurements that the Al addition results in an acceleration whereas Si addition leads to a retardation in bainite transformation kinetics. The addition of Al retards the decomposition of austenite into pearlite and carbides at holding temperatures higher than450℃ whereas Si retards the decomposition of austenite into carbides at temperatures lower than 450℃.Consequently, the Al-added bainitic steel has a better strength-elongation combination at bainitic holding temperatures higher than 450℃ while Si-added steel has a better strength-elongation combination at temperatures lower than 450℃. The higher yield strength of Al-added steel is mainly attributed to its finer bainitic lath. The higher tensile strength of Si-added steel is not only related to the stronger contribution of Si on work hardening during deformation, but also due to the higher volume fraction of martensite or martensite/austenite（MA） blocks in all heat treatment conditions, as well as the lower mechanical stability of retained austenite in this steel.

Phase Transformation and Mechanical Properties of an Ultrahigh Strength Steel

The present study deals with the development of a low carbon high strength steel by thermomechanical controlled processing on a pilot scale.The continuous cooling transformation has yielded a flat top "C" curve with the phase field occupied by a mixture of bainite and martensite.The microstructure of water quenched steel essentially consists of highly dislocated lath martensite along with fine (Ti,Nb)CN precipitates and twins.High strength steel with 1217-1298 MPa yield strength and 1372-1513 MPa ultimate tensile strength along with 16-12% total elongation has been obtained in the range of 850 to 750℃ finish rolling temperature.The impact toughness value in the range of 45-72J was also achieved in the present steel.

Machine learning for integrating combustion chemistry in numerical simulations

A strategy based on machine learning is discussed to close the gap between the detailed description of combustion chemistry and the numerical simulation of combustion systems.Indeed,the partial differential equations describ-ing chemical kinetics are stiffand involve many degrees of freedom,making their solving in three-dimensional unsteady simulations very challenging.It is discussed in this work how a reduction of the computing cost by an order of magnitude can be achieved using a set of neural networks trained for solving chemistry.The ther-mochemical database used for training is composed of time evolutions of stochastic particles carrying chemical species mass fractions and temperature according to a turbulent micro-mixing problem coupled with complex chemistry.The novelty of the work lies in the decomposition of the thermochemical hyperspace into clusters to facilitate the training of neural networks.This decomposition is performed with the Kmeans algorithm,a local principal component analysis is then applied to every cluster.This new methodology for combustion chemistry reduction is tested under conditions representative of a non-premixed syngas oxy-flame.

Thermal response of steel framing members in open car park fires

For open car park structures,adopting a performance-based structural fire design is often justified and allowed because the fire does not reach flashover.However,this design approach requires an accurate assessment of temperatures in structural members exposed to car fires.This paper describes a numerical study on the thermal exposure on steel framing members in open car park fires.Steel temperatures are computed by the coupling of computational fluid dynamics and finite element modeling,and by analytical models from the Eurocodes.In addition,the influence of galvanization on the steel temperature evolution is assessed.Results show that temperatures in unprotected beams and columns are influenced by the section geometry,car fire scenario,modeling approach,and use of galvanization.Galvanization slightly delays and reduces peak temperature.Regarding the different models,CFD-FEM(CFD:computational fluid dynamics,FEM:finite-element method)coupled models predict lower temperatures than the Hasemi model,because the latter conservatively assumes that the fire flame continuously touches the ceiling.Further,the Hasemi model cannot account for the effect of reduced emissivity from galvanization on the absorbed heat flux.Detailed temperature distributions obtained in the steel members can be used to complete efficient structural fire designs based on the member sections,structure layout,and use of galvanization.

Effect of Nb on Microstructure Evolution in Cold Rolled Dual-Phase Steels:Interaction of Recovery,Recrystallization and Phase Transformations

The effects of Nb addition,individually and in combination with Ti,were evaluated over a range of coiling temperatures.Coiling temperature influences the ratio of soluble and precipitated Nb in the hot rolled steel containing 0.08 % C and 2.2 % Mn.Nb bearing precipitates can co-precipitate on TiN and impact the microstructure and mechanical properties of the steel after annealing treatment.Microstructure characterization revealed that recovery and recrystallization processes preceded austenite formation.The effects of Nb on austenite formation in cold rolled steels during heating and isothermal holding and on austenite decomposition during subsequent cooling were investigated using dilatometry.The addition of Nb retarded ferrite recrystallization starting temperature,but had no significant effect on the starting temperature of austenite formation during heating.The Nb addition also accelerated austenite formation once the transformation started,and was beneficial for the formation of a finer and homogeneous microstructure.

Compact representations of microstructure images using triplet networks

The microstructure of a material,typically characterized through a set of microscopy images of two-dimensional cross-sections,is a valuable source of information about the material and its properties.Every pixel of the image is a degree of freedom causing the dimensionality of the information space to be extremely high.This makes it difficult to recognize and extract all relevant information from the images.Human experts circumvent this by manually creating a lower-dimensional representation of the microstructure.However,the question of how a microstructure image can be best represented remains open.From the field of deep learning,we present triplet networks as a method to build highly compact representations of the microstructure,condensing the relevant information into a much smaller number of dimensions.We demonstrate that these representations can be created even with a limited amount of example images,and that they are able to distinguish between visually very similar microstructures.We discuss the interpretability and generalization of the representations.Having compact microstructure representations,it becomes easier to establish processing–structure–property links that are key to rational materials design.