With the development of modern weapon systems, the requirements for the survivability of ammunition in various complex environments have been continuously increasing. During the processes of storage, flight, and combat, ammunition may be subjected to extreme impact loads such as high-speed impacts, shock waves, bullet and fragment impacts. The external impacts can induce plastic deformation and fracture of the ammunition casing, and even detonate the internal explosives. These responses involve complex phenomena including impact loading, thermo-mechanical coupling of materials, chemical reactions of explosives, and blast effects, representing a typical dynamic response problem of reactive materials under extreme thermo-mechanical coupling conditions. Accurately predicting the responses of ammunition under impact loading is critical for its design optimization and safety assessment. Based on the Hot Optimal Transportation Meshfree (HOTM) method, a meshfree numerical approach was proposed to accurately predict the ammunition responses under different impact loadings. Meanwhile, a thermo-mechanical-chemical coupling constitutive model of explosives was established, which took the effects of temperature and pressure on the explosive’s chemical reaction and detonation into account. The Arrhenius thermal-chemical reaction coupling model for explosive initiation and the Lee-Tarver three-term pressure ignition model induced by local high pressure were integrated to accurately simulate the different initiation mechanisms of explosives under varying impact velocities, thereby predict complex physical phenomena during the impact loading of ammunition. These phenomena include high-speed contact, large plastic deformation of the metal casing, material fracture, heat conduction, explosive initiation, and the expansion work performed by chemical reaction products. Taking the numerical simulations of two typical impact scenarios—bullet impact on ammunition at 850 m/s and fragment impact at 1850 m/s—as examples, the influence of impact velocity on the initiation mechanisms of explosives and the overall response of ammunition was analyzed, with comparisons made against relevant experimental results. The proposed approach and findings provide reliable technical support for the optimization of impact-resistant design and safety assessment of ammunition.

We present a fully coupled hydro-thermomechanical framework for multiphase model of porous media under extreme thermomechanical conditions, possibly involving extremely large deformation, heat conduction, phase transition and internal flow. The proposed computational framework combines the hot optimal transportation meshfree (HOTM) method and a meshfree formulation of Darcy’s law. In specific, the optimal transportation theory is introduced for temporal discretization, while material-point sampling method is employed for spatial discretization of the porous media. The linear momentum and energy conservation are formulated in the Lagrangian configuration and jointly solved in the HOTM framework to predict the solid-skeleton deformation and the temperature evolution in porous media. Meanwhile, the mass conservation and Darcy’s law are formulated in the current configuration at the material-point level and solved via a weighted residual method to predict the internal fluid flow and the porosity distribution in porous media. The detailed formulation of the computational framework is stated and validated. Then, we focus on a particular application: the hot-forming process of resin-based friction composites. In this simulation, the resin-based matrix is modeled as a continuous porous medium, while particles and fibers are modeled as explicit spheres and cylinders embedded in the porous matrix. Simulations with various loading conditions are conducted to investigate the effects of loading parameters on the internal fluid flow and porosity in the product. The sensitivity of product’s porosity on loading conditions including pressure and temperature is further studied.

This research investigates thermal stress and deformation behavior in a vertically compressed shear-flexible microplate designed for aerobic fitness applications using a nonlocal continuum framework and virtual displacement principles. The developed analytical framework serves as a functional model for optimizing exercise equipment design. Three-dimensional material relationships are established through fundamental elasticity principles, incorporating thermally induced deformations caused by vertical thermal gradients. Following resolution of the governing equations via a series expansion method, comprehensive parameter evaluations assess how temperature variations and microscale effects influence structural responses. Computational outcomes illustrate correlations between thermal loading profiles, material length parameters, and mechanical performance metrics. Practical implications of this model relate to enhancing biomechanical efficiency in athletic training apparatus through tailored microstructural adaptations.

In this study, we proposed alternative spreading techniques aimed at enhancing the powder bed properties in powder bed fusion additive manufacturing, utilizing discrete element simulations. Our findings revealed significant alterations in the powder spreading regime depending on the adopted spreading strategies. In powder spreading with two blades, the climbing regime in the powder pile was eliminated due to the high compressive condition. The powder spreading with two blades can enhance the homogeneity of the powder bed by maintaining a steady powder pile throughout the spreading process. The spreading with the funnel resulted in superior packing density and reduced surface roughness by effectively mitigating surface pores and loosely packed regions. The force arch formation in spreading with the funnel was suppressed throughout the spreading process, facilitated by rapid kinetic energy dissipation within the downsized powder pile. The high cohesive force of powders reduces packing density during the conventional spreading process, promoting the formation of surface pores. In spreading with the funnel, the influence of cohesive force on force arch formation and packing density was alleviated. Compared to conventional spreading techniques, spreading with the funnel improved both packing density and homogeneity of the powder bed under various gravity magnitudes. Therefore, it was demonstrated that the powder bed quality can be improved by employing the powder spreading with funnel, regardless of powder properties or gravity levels.

Multiple myeloma (MM) is an incurable hematological malignancy. The bone marrow immune microenvironment plays a crucial role in MM progression. Our previous studies have shown that natural killer (NK) cell function is depleted in the bone marrow microenvironment of patients with MM. Therefore, it is urgent to explore the mechanisms underlying NK cell depletion and identify potential therapeutic targets. In this study, we focused on the mechanisms and potential therapeutic targets of MM osteoblasts that promote bone marrow NK cell depletion. The receptor activator of NF-kappa B (RANK) expression in bone marrow NK cells of patients with MM was significantly higher than that in normal controls. Serum receptor activator of NF-kappa B ligand (RANKL) levels in patients with MM also significantly higher than those in normal controls. MM cells can induce RANK expression in NK cells. Moreover, it is osteoblasts-not bone marrow mesenchymal stem cells-that secrete more RANKL. Blocking RANKL with denosumab resulted in increased CD107a expression, decreased KIR3DL1 expression, and increased release of perforin and granzyme B in NK cells. In addition, apoptosis was significantly increased in MM cells. Bone marrow osteoblasts in patients with MM may inhibit NK cell function via RANK/RANKL. Furthermore, denosumab combined with lenalidomide or pomalidomide can improve bone marrow NK cell function in these patients.

Background Few studies have focused on the development of multiple myeloma (MM)-specific immunotherapies. Tumor immunogenic cell death (ICD), triggered by damage-associated molecular patterns, may enhance MM-specific antitumor activity, offering a potential treatment strategy.Methods This study confirms that combining reactive oxygen species (ROS)-endoplasmic reticulum stress (ERS) and pyroptosis-inducers (ROS-ERS inducer 1 (REI) and Quillaja saponaria fraction 21 (QS-21), respectively) activates specific anti-MM immunity. MM cell lines were treated with REI and QS-21 alone or in combination and cytotoxicity and apoptosis were examined. ICD markers were identified, including calreticulin, ATP, heat shock protein 70, and high mobility group box 1. Additionally, changes in mitochondrial damage, endoplasmic reticulum stress, pyroptosis markers, and immune markers of dendritic cell (DC) maturation and T-cell activation were assessed both in vitro and in vivo.Results ROS-ERS combined with pyroptosis significantly induces MM cell apoptosis and enhances ICD marker activation. The combination treatment induces severe mitochondrial damage and endoplasmic reticulum stress, further promoting pyroptosis and MM-specific T-cell activation. In vivo, the combination treatment reduces tumor growth and improves DC and T-cell activation.Conclusions Thus, ROS-ERS inducers and pyroptosis inducers together significantly enhance the immunogenic response against MM, providing a promising strategy for MM treatment by activating powerful specific T-cell antitumor immunity.

Over the last two decades, meshfree Galerkin methods have become increasingly popular in solid and fluid mechanics applications. A variety of these methods have been developed, each incorporating unique meshfree approximation schemes to enhance their performance. In this study, we examine the application of the Moving Least Squares and Local Maximum-Entropy (LME) approximations within the framework of Optimal Transportation Meshfree for solving Galerkin boundary-value problems. We focus on how the choice of basis order and the non-negativity, as well as the weak Kronecker-delta properties of shape functions, influence the performance of numerical solutions. Through comparative numerical experiments, we evaluate the efficiency, accuracy, and capabilities of these two approximation schemes. The decision to use one method over the other often hinges on factors like computational efficiency and resource management, underscoring the importance of carefully considering the specific attributes of the data and the intrinsic nature of the problem being addressed.

Immune effector cells in patients with multiple myeloma (MM) are at the forefront of many immunotherapy treatments, and several methods have been developed to fully utilise the antitumour potential of immune cells. T and NK cell-derived immune lymphocytes both expressed activating NK receptor group 2 member D(NKG2D). This receptor can identify eight distinct NKG2D ligands (NKG2DL), including major histocompatibility complex class I (MHC) chain-related protein A and B (MICA and MICB). Their binding to NKG2D triggers effector roles in T and NK cells. NKG2DL is polymorphic in MM cells. The decreased expression of NKG2DL on the cell surface is explained by multiple mechanisms of tumour immune escape. In this review, we discuss the mechanisms by which the NKG2D/NKG2DL axis regulates immune effector cells and strategies for promoting NKG2DL expression and inhibiting its release in multiple myeloma and propose therapeutic strategies that increase the expression of NKG2DL in MM cells while enhancing the activation and killing function of NK cells.

The pharmaceutical industry has experienced a remarkable increase in the use of subcutaneous injection of monoclonal antibodies (mAbs), attributed mainly to its advantages in reducing healthcare-related costs and enhancing patient compliance. Despite this growth, there is a limited understanding of how tissue mechanics, physiological parameters, and different injection devices and techniques influence the transport and absorption of the drug. In this work, we propose a high-fidelity computational model to study drug transport and absorption during and after subcutaneous injection of mAbs. Our numerical model includes large-deformation mechanics, fluid flow, drug transport, and blood and lymphatic uptake. Through this computational framework, we analyze the tissue material responses, plume dynamics, and drug absorption. We analyze different devices, injection techniques, and physiological parameters such as BMI, flow rate, and injection depth. Finally, we compare our numerical results against the experimental data from the literature.

BACKGROUND AND OBJECTIVE:Subcutaneous injection of biotherapeutics has attracted considerable attention in the pharmaceutical industry. However, there is limited understanding of the mechanisms underlying the absorption of drugs with different molecular weights and the delivery of drugs from the injection site to the targeted tissue. METHODS:We propose the MPET2-mPBPK model to address this issue. This multiscale model couples the MPET2 model, which describes subcutaneous injection at the local tissue scale from a biomechanical view, with a post-injection absorption model at injection site and a minimal physiologically-based pharmacokinetic (mPBPK) model at whole-body scale. Utilizing the principles of tissue biomechanics and fluid dynamics, the local MPET2 model provides solutions that account for tissue deformation and drug absorption in local blood vessels and initial lymphatic vessels during injection. Additionally, we introduce a model accounting for the molecular weight effect on the absorption by blood vessels, and a nonlinear model accounting for the absorption in lymphatic vessels. The post-injection model predicts drug absorption in local blood vessels and initial lymphatic vessels, which are integrated into the whole-body mPBPK model to describe the pharmacokinetic behaviors of the absorbed drug in the circulatory and lymphatic system. RESULTS:We establish a numerical model which links the biomechanical process of subcutaneous injection at local tissue scale and the pharmacokinetic behaviors of injected biotherapeutics at whole-body scale. With the help of the model, we propose an explicit relationship between the reflection coefficient and the molecular weight and predict the bioavalibility of biotherapeutics with varying molecular weights via subcutaneous injection. CONCLUSION:The considered drug absorption mechanisms enable us to study the differences in local drug absorption and whole-body drug distribution with varying molecular weights. This model enhances the understanding of drug absorption mechanisms and transport routes in the circulatory system for drugs of different molecular weights, and holds the potential to facilitate the application of computational modeling to drug formulation.

Printed electronics are widely used in wearable tech, IoT, and medical devices, and reliable sintering methods are essential for achieving optimal electrode conductivity. However, existing sintering models are often based on trial-and-error or past experience, highlighting the need for a reliable numerical model to improve the process. Traditional phase-field sintering models are limited by factors such as small mesh size requirements, high computational expenses for large-scale simulations, and high mesh sensitivity. In this article, we introduce a new meshfree phase field model based on the recent hot optimal transform meshfree (HOTM) method to simulate nanoparticle sintering processes efficiently and accurately. We use the Galerkin method to develop variational forms for the Cahn–Hillard and the Allen–Chan equation of the phase-field model. In addition, we apply the Local maximum entropy (LEM) shape function to construct a Node-Material Point framework. Finally, we present two efficiency improvement schemes and MPI parallel computation that enable the model to perform large-scale simulations. After several performance tests, we demonstrate its efficiency and accuracy by presenting both 2D and 3D simulation cases in comparison to actual sintering behaviors of the nanoparticles.

The MPET2 model couples the multi-network poroelastic theory (MPET) with solute transport equations and provides predictions of the material deformation, fluid dynamics, and solute transport in different compartments of a deformable multiple-porosity medium. MPET2 offers a comprehensive framework for understanding complex porous media across multiple disciplines. Examples of its applications include studying rock formations, soil mechanics and subsurface reservoirs, investigating biological tissues, modeling groundwater flow and contaminant transport, and optimizing the design of porous materials. Despite the wide range of applications of the model, its numerical discretization has received little attention. Here we propose a stabilized formulation of the MPET2 model. To address the unique challenges posed by the discretization of the MPET2 model, we use multiple techniques including the Fluid Pressure Laplacian stabilization, Streamline Upwind Petrov–Galerkin stabilization, and discontinuity capturing. Our spatial discretization is based on Isogeometric Analysis with higher-order continuity basis functions. The fully discretized governing equations are solved simultaneously with a monolithic algorithm. We perform a convergence study of the proposed formulation. Then, we conduct a series of simulations of subcutaneous injection of monoclonal antibodies under different injection conditions. Our simulations show that the stabilized MPET2 formulation can provide oscillation-free solutions for tissue deformation, fluid flow in the interstitial tissue, blood vessels, and lymphatic vessels, drug absorption in blood vessels and lymphatic vessels, as well as drug transport in each compartment. We also study the effects of different injection conditions on drug absorption, showing the potential of the proposed model and algorithm in the future optimization of injection strategy.

This book shares insights on post-processing techniques adopted to achieve precision-grade surfaces of additive manufactured metals including material characterization techniques and the identified material properties. Post-processes are discussed from support structure removal and heat treatment to the material removal processes including hybrid manufacturing. Also discussed are case studies on unique applications of additive manufactured metals as an exemplary of the considerations taken during post-processing design and selection. Addresses the critical aspect of post-processing for metal additive manufacturing Provides systematic introduction of pertinent materials Demonstrates post-process technique selection with the enhanced understanding of material characterization methods and evaluation Includes in-depth validation of ultra-precision machining technology Reviews precision fabrication of industrial-grade titanium alloys, steels, and aluminium alloys, with additive manufacturing technology The book is aimed at researchers, professionals, and graduate students in advanced manufacturing, additive manufacturing, machining, and materials processing.

Subcutaneous injection of monoclonal antibodies (mAbs) has attracted much attention in the pharmaceutical industry. During the injection, the drug is delivered into the tissue producing strong fluid flow and tissue deformation. While data indicate that the drug is initially uptaken by the lymphatic system due to the large size of mAbs, many of the critical absorption processes that occur at the injection site remain poorly understood. Here, we propose the MPET2 approach, a multi-network poroelastic and transport model to predict the absorption of mAbs during and after subcutaneous injection. Our model is based on physical principles of tissue biomechanics and fluid dynamics. The subcutaneous tissue is modeled as a mixture of three compartments, i.e., interstitial tissue, blood vessels, and lymphatic vessels, with each compartment modeled as a porous medium. The proposed biomechanical model describes tissue deformation, fluid flow in each compartment, the fluid exchanges between compartments, the absorption of mAbs in blood vessels and lymphatic vessels, as well as the transport of mAbs in each compartment. We used our model to perform a high-fidelity simulation of an injection of mAbs in subcutaneous tissue and evaluated the long-term drug absorption. Our model results show good agreement with experimental data in depot clearance tests.

Subcutaneous injection of monoclonal antibodies (mAbs) has experienced unprecedented growth in the pharmaceutical industry due to its benefits in patient compliance and cost-effectiveness. However, the impact of different injection techniques and autoinjector devices on the drug’s transport and uptake is poorly understood. Here, we develop a biphasic large-deformation chemomechanical model that accounts for the components of the extracellular matrix that govern solid deformation and fluid flow within the subcutaneous tissue: interstitial fluid, collagen fibers and negatively charged proteoglycan aggregates. We use this model to build a high-fidelity representation of a virtual patient performing a subcutaneous injection of mAbs. We analyze the impact of the pinch and stretch methods on the injection dynamics and the use of different handheld autoinjector devices. The results suggest that autoinjector base plates with a larger device-skin contact area cause significantly lower tissue mechanical stress, fluid pressure and fluid velocity during the injection process. Our simulations indicate that the stretch technique presents a higher risk of intramuscular injection for autoinjectors with a relatively long needle insertion depth.

We present the method of direct van der Waals simulation (DVS) to study computationally flows with liquid-vapor phase transformations. Our approach is based on a discretization of the Navier-Stokes-Korteweg equations, which couple flow dynamics with van der Waals’ nonequilibrium thermodynamic theory of phase transformations, and opens an opportunity for first-principles simulation of a wide range of boiling and cavitating flows. The proposed algorithm enables unprecedented simulations of the Navier-Stokes-Korteweg equations involving cavitating flows at strongly under-critical conditions and 𝒪(105) Reynolds number. The proposed technique provides a pathway for a fundamental understanding of phase-transforming flows with multiple applications in science, engineering, and medicine.

EZH2, a member of the polycomb repressive complex 2, induces trimethylation of the downstream gene at the histone three lysine 27 (H3K27me3) position to inhibit tumor cell proliferation. Here, we showed that the apoptosis rate and apoptotic protein expression increased after EZH2 inhibition, whereas key molecules of the NF-κB signaling pathway and the downstream target genes were inhibited. Additionally, the expression of CD155, a TIGIT high-affinity ligand in multiple myeloma (MM) cells, was decreased by the mTOR signaling pathway. Furthermore, the combination of EZH2 inhibitor and TIGIT monoclonal antibody blockade enhanced the anti-tumor effect of natural killer cells. In summary, the EZH2 inhibitor not only plays an anti-tumor role as an epigenetic drug, but also enhances the anti-tumor effect of the TIGIT monoclonal antibody by affecting the TIGIT-CD155 axis between NK cells and MM cells, thus providing new ideas and theoretical basis for the treatment of MM patients.

A fully coupled thermomechanical computational framework based on the Hot Optimal Transportation Meshfree (HOTM) method is presented to derive the process-microstructure-properties correlation for resin-based friction composites manufactured by hot pressing technique. The raw material is considered as reinforcing fibers and strengthening particles explicitly embedded in a continuum porous media. The manufacturing process is modeled as the raw material experiencing extremely large compression under applied pressure and temperature boundary conditions to predict the formation and evolution of the composite's microstructure. A chemo-thermo-mechanical constitutive model is proposed to describe the dynamic response of the matrix material involving large inelastic deformation, resin melting and polymerization. The microstructure of the final product produced by hot pressing processes is predicted by solving the deformation, temperature and curing degree of the raw material using the HOTM method. The computational framework is validated by comparing the calculated fiber orientation distribution in the friction materials to experimental measurements under various processing conditions. The sensitivity of composite's mechanical properties on the fiber orientation is further studied by the proposed numerical method and experiments.

A phase-aware constitutive model is developed and integrated with the meshfree simulations to study the failure mechanisms of space structural materials under the oblique hypervelocity impact of ice. The proposed constitutive model covers material’s dynamic behavior in a wide range of temperature, pressure, and strain rates. The numerical analysis combines the Hot Optimal Transportation Meshfree method with the EigenErosion algorithm to explicitly account for large deformation, brittle and ductile failure, phase transition, and debris cloud formation in the target materials and ice projectile. Specifically, the surface erosion and crater formation in the target under different impact speeds and angles are characterized by the damage’s shapes, depth, and length. The predicted crater depths in the Al6061 targets are validated by the Cour-Palais empirical model. It is evident that the damage to the space structural material by ice particles results from the competition between fracture, plasticity, and phase transition in the materials. The impact angle and velocity determine the crater deformation and the potential thread of the ejected debris.