A Mechanism-Based Approach for Predicting Ductile Fracture of Metallic Alloys

Ductile fracture in metallic alloys often follows a multi-step failure process involving void nucleation, growth and coalescence. Because of the difference in orders of magnitude between the size of the finite element needed to resolve the microscopic details and the size of the engineering structures, homogenized material models, which exhibits strain softening, are often used to simulate the crack propagation process. Various forms of porous plasticity models have been developed for this purpose. Calibration of these models requires the predicted macroscopic stress-strain response and void growth behavior of the representative material volume to match the results obtained from detailed finite element models with explicit void representation. A series of carefully designed experiments combined with finite element analyses of these specimens can also be used to calibrate the model parameters. As an example, a numerical procedure is proposed to predict ductile crack growth in thin panels of a 2024-T3 aluminum alloy. The calibrated computational model is applied to simulate crack extension in specimens having various initial crack configurations and the numerical predictions agree very well with experimental measurements

Recent Development in the Weibull Stress Model for Prediction of Cleavage Fracture in Ferritic Steels

This paper reviews recent developments in the Weibull stress model for prediction of cleavage fracture in ferritic steels. The procedure to calibrate the Weibull stress parameters builds upon the toughness scaling model between two crack configurations having different constraint levels and eliminates the recently discovered non-uniqueness that arises in calibrations using only fracture toughness data obtained under small scale yielding (SSY) conditions. The introduction of a non-zero threshold value for Weibull stress in the expression for cumulative failure probability is consistent with the experimental observations that there exists a minimum toughness value for cleavage fracture in ferritic steels, and brings numerical predictions of the scatter in fracture toughness data into better agreement with experiments. The calibrated model predicts accurately the toughness distributions for a variety of crack configurations including surface crack specimens subject to different combinations of bending tension

Enabling and Understanding Failure of Engineering Structures Using the Technique of Cohesive Elements

In this paper, we describe a cohesive zone model for the prediction of failure of engineering solids and/or structures. A damage evolution law is incorporated into a three-dimensional, exponential cohesive law to account for material degradation under the influence of cyclic loading. This cohesive zone model is implemented in the finite element software ABAQUS through a user defined subroutine. The irreversibility of the cohesive zone model is first verified and subsequently applied for studying cyclic crack growth in specimens experiencing different modes of fracture and/or failure. The crack growth behavior to include both crack initiation and crack propagation becomes a natural outcome of the numerical simulation. Numerical examples suggest that the irreversible cohesive zone model can serve as an efficient tool to predict fatigue crack growth. Key issues such as crack path deviation, convergence and mesh dependency are also discussed

Numerical Modeling of the Constraint Effects on Cleavage Fracture Toughness

Cleavage fracture has been an important subject for engineers primarily because of its catastrophic nature and consequences. Experimental studies of cleavage fracture did reveal a considerable amount of scatter and provided evidence of noticeable constraint effects. This did provide the motivation for the development of statistical-based and micromechanics-based methods in order to both study and analyze the problem. The Weibull stress model, which is based on the weakest link statistics, uses two parameters (m and σ u) to effectively describe the inherent distribution of the micro-scale cracks once plastic deformation has occurred and to concurrently define the relationship between the macro-scale and micro-scale driving forces for cleavage fracture. In this paper, we present the results of a recent study at evaluating the constraint effects on cleavage fracture toughness. This was done numerically using a constraint function (g(M)) derived from the Weibull stress model. The non-dimensional function (g(M)) describes the evolution of constraint loss effects on fracture toughness relative to the reference plane-strain, small scale yielding (SSY) condition (T-stress = 0). We performed detailed finite element analyses of single-edge notched bending specimens and computed the non-dimensional g(M) functions for them. The g(M) function varies with (i) the Weibull modulus, (ii) material flow properties, and (iii) specimen geometry, but not with absolute size of the test specimen. Knowing the g-function, the fracture driving force curve can be constructed for each absolute size of interest

Identification of tumor mutation burden-associated molecular and clinical features in cancer by analyzing multi-omics data

BackgroundTumor mutation burden (TMB) has been recognized as a predictive biomarker for immunotherapy response in cancer. Systematic identification of molecular features correlated with TMB is significant, although such investigation remains insufficient.MethodsWe analyzed associations of somatic mutations, pathways, protein expression, microRNAs (miRNAs), long non-coding RNAs (lncRNAs), competing endogenous RNA (ceRNA) antitumor immune signatures, and clinical features with TMB in various cancers using multi-omics datasets from The Cancer Genome Atlas (TCGA) program and datasets for cancer cohorts receiving the immune checkpoint blockade therapy.ResultsAmong the 32 TCGA cancer types, melanoma harbored the highest percentage of high-TMB (≥ 10/Mb) cancers (49.4%), followed by lung adenocarcinoma (36.9%) and lung squamous cell carcinoma (28.1%). Three hundred seventy-six genes had significant correlations of their mutations with increased TMB in various cancers, including 11 genes (ARID1A, ARID1B, BRIP1, NOTCH2, NOTCH4, EPHA5, ROS1, FAT1, SPEN, NSD1,and PTPRT) with the characteristic of their mutations associated with a favorable response to immunotherapy. Based on the mutation profiles in three genes (ROS1, SPEN, and PTPRT), we defined the TMB prognostic score that could predict cancer survival prognosis in the immunotherapy setting but not in the non-immunotherapy setting. It suggests that the TMB prognostic score’s ability to predict cancer prognosis is associated with the positive correlation between immunotherapy response and TMB. Nine cancer-associated pathways correlated positively with TMB in various cancers, including nucleotide excision repair, DNA replication, homologous recombination, base excision repair, mismatch repair, cell cycle, spliceosome, proteasome, and RNA degradation. In contrast, seven pathways correlated inversely with TMB in multiple cancers, including Wnt, Hedgehog, PI3K-AKT, MAPK, neurotrophin, axon guidance, and pathways in cancer. High-TMB cancers displayed higher levels of antitumor immune signatures and PD-L1 expression than low-TMB cancers in diverse cancers. The association between TMB and survival prognosis was positive in bladder, gastric, and endometrial cancers and negative in liver and head and neck cancers. TMB also showed significant associations with age, gender, height, weight, smoking, and race in certain cohorts.ConclusionsThe molecular and clinical features significantly associated with TMB could be valuable predictors for TMB and immunotherapy response and therefore have potential clinical values for cancer management

Electroacupuncture Improves Cerebral Vasospasm and Functional Outcome of Patients With Aneurysmal Subarachnoid Hemorrhage

Cerebral vasospasm is the major cause of a poor outcome after aneurysmal subarachnoid hemorrhage (aSAH), and effective treatments for vasospasm are limited. The purpose of this study was to research the impact of electroacupuncture (EA) on cerebral vasospasm and the outcomes of patients with aSAH. A total of 60 age- and sex-matched aSAH patients were collected from Ningbo First Hospital between December 2015 and June 2017. All patients were given a basic treatment of nimodipine and randomized into two groups. The study group was treated with EA therapy on the Baihui (GV20) acupoint, and the control group was given mock transcutaneous electrical nerve stimulation. Cerebral vasospasm was measured by computed tomographic perfusion (CTP) and transcranial doppler (TCD). The mean flow velocity (MFV) in the middle cerebral artery (MCA), cerebral blood flow (CBF), cerebral blood volume (CBV), and mean transit time (MTT) of the patients were analyzed. The CBV and MTT exhibited significant differences between the study and control groups on the 1st (p = 0.026 and p = 0.001), 7th (p = 0.020 and p < 0.001), and 14th (p = 0.001 and p < 0.001) day after surgery, whereas CBF exhibited statistical significance only on the 14th day after surgery (p = 0.002). The MFV in MCA were significantly reduced after EA treatment in all patients (all p < 0.001). Additionally, the MFV in the MCA in patients treated with EA were considerably reduced compared with those of the control group (3rd day p = 0.046; 5th day, p = 0.010; 7th day, p < 0.001). Moreover, better outcomes were noted in the EA-treated group for the 1st month (p < 0.001) and 3rd month (p = 0.001) after surgery than in the control group. In conclusion, EA represents a potential method to treat cerebral vasospasm after aSAH and can improve the outcomes of patients with aSAH