This paper presents a design-oriented framework for engineering internal surface roughness in additively manufactured (AM) polymer pipes intended for mixing and flow conditioning. The framework takes advantage of the natural layer surface texture generated by AM processes, with a focus on thermoplastic fused filament fabrication (FFF). The proposed approach integrates geometric design rules, AM and material constraints, and both computational and experimental evaluation. The objective is to design functional roughness patterns on internal pipe walls using only the printed layer lines, while the constraints come from the limitations of the manufacturing process and material used. Because of this, the framework incorporates manufacturability filters and material selection guidelines to ensure that proposed roughness features exceed the geometric noise of the printing process and remain stable under operating conditions. An illustrative case study was done to explore and demonstrate the framework, which included computational fluid dynamics (CFD) and experimental tests. The pipes used were polylactide (PLA), manufactured with uniform ridge heights and tested under transitional flow conditions; the effect of ridge height at different height scales was the main exploration variable. The results illustrate the major elements of the framework and suggest the existence of a minimum effective roughness threshold for transitional flow. The study establishes a foundation for the design of more advanced roughness patterns for applications in mixing, heat transfer, and general flow conditioning.

Poly(3-hydroxybutyrate-co-3-hydroxyhexanoate) (PHBH) is a biodegradable polyester with strong potential for marine and packaging applications common for thermoplastic polymers, yet its performance after being additively manufactured remains largely unknown. This study investigates the mechanical, density, and hardness properties of PHBH processed with fused filament fabrication (FFF) compared with injection-molded benchmarks, with a focus on process-property relationships and useful information for design applications. FFF-printed samples were produced under varying nozzle temperature, print speed, and layer height following a full-factorial experimental design, and tested for elastic modulus, ultimate tensile strength, elongation at break, density, and Shore D hardness. Five replications of 27 factor combinations were used for the printed samples, in addition to the injection-molded samples, for a total of 792 data points from 312 individual samples. Crystallinity values for the raw material and molded and printed samples were evaluated and found to not vary significantly for any of the samples. Compared with injection-molded parts, FFF parts exhibited lower strength and elongation but comparable or higher modulus under certain conditions. In particular, the differences in properties were 5%-17% (with the exception of elongation) instead of 40%-70% seen with many other FFF materials. The differences were attributed to shorter thermal holding times in the extruder, layer-wise deposition, and reduced consolidation. The density and hardness were generally lower in the printed parts, reflecting interlayer voids and limited polymer chain diffusion. The results highlight parameter combinations that improve interlayer bonding while avoiding thermal degradation, providing a processing window for reliable FFF production of PHBH. These findings support the viability of PHBH in additive manufacturing, enabling on-demand fabrication of biodegradable components for short-lifecycle and marine-degradable applications.

Polymeric and bioinspired adhesive interfaces exhibit complex mechanical behavior governed by time-dependent relaxation, temperature-dependent properties, and progressive degradation under repeated attachment–detachment cycles. Existing cohesive zone models typically address these mechanisms in isolation, limiting their predictive capability under coupled loading conditions. This work presents a unified thermo-viscoelastic cohesive zone model that simultaneously captures viscoelastic relaxation, temperature-dependent property evolution, and cyclic fatigue degradation within a single constitutive framework. The model extends the Park–Paulino–Roesler (PPR) potential-based cohesive law by incorporating (i) a standard-linear-solid viscoelastic element to represent time-dependent energy dissipation, (ii) a phenomenological degradation model to account for progressive property loss over repeated cycles, and (iii) a sigmoidal transition function to interpolate cohesive properties smoothly between glassy and rubbery states. The model is implemented as a user-element subroutine in ABAQUS finite element software. The material parameters were calibrated from mushroom–mushroom interlocking tape experiments at 20 °C and 60 °C under Mode I loading and validated against double-cantilever beam tests under monotonic, cyclic, and creep-type loading. The model accurately reproduces experimental force-displacement curves, cyclic degradation trends, and time-dependent crack growth, with a discrepancy of <10% in the predicted and measured peak force and dissipated work. Overall, this work provides a unified and experimentally validated cohesive modeling framework for polymeric interlocking interfaces that exhibit coupled rate, thermal, and cycle-dependent behavior.

Expeditionary environments (such as remote exploration missions, forward military operations, and disaster response zones) demand adaptive manufacturing solutions to support vehicle sustainment in the absence of traditional supply chains. This work introduces a conceptual mathematical framework for modeling the constraints and tradeoffs inherent to expeditionary manufacturing, with a focus on vehicle repair and spare parts fabrication using low-energy and simple automated systems including desktop-scale 3D printers and CNC machines. The model integrates key variables such as energy availability, material transport cost, fabrication time, and environmental limitations to support rapid decision-making on part manufacturability and in-field feasibility. A case study involving the on-demand production of some common wear and failure parts on a vehicle, including suspension components and the water pump, is used to demonstrate how this framework can guide the selection of suitable manufacturing technologies, part redesign or repair for field printing. This modeling approach highlights how predictive modeling can optimize both component geometry and process parameters to meet requirements while minimizing energy expenditure and logistics overhead. This work informs future efforts in resilient vehicle system design by embedding manufacturability considerations into the early stages of development, particularly for platforms intended for deployment in expeditionary environments. It offers practical guidance to designers, logisticians, and mission planners seeking to integrate field-capable manufacturing into vehicle lifecycle support.

Off-road autonomous vehicle systems must be able to operate across unstructured and variable terrain while avoiding obstacles. This presents significant challenges in vehicle and control system design, especially for less conventional platforms such as 6×4 vehicles. While forward driving autonomy has developed and matured in recent years, effective reverse navigation remains an under-explored area of vehicle co-design. Reversing 6×4 vehicles have limited rear steering authority, an extended wheelbase, and asymmetric traction, which introduce complex dynamics into any control system that is used. To address this need, a robust and experimentally validated fuzzy logic control architecture for 6×4 reverse navigation was developed during the course of this project. This architecture incorporates both near-field and long-range path data with adaptive outputs controlling steering and velocity based on a rule base that covers the whole vehicle state space. This method has low computational cost and is robust to terrain changes, wheel slip, and actuator lag. To accomplish this, the controller coevolves with the vehicle design parameters, making this an effective co-design strategy. The vehicle design constraints are embedded into the controller through constraint-aware membership functions and rule tuning, reducing the need for terrain-specific calibration. The architecture is modular and scalable across numerous similar platforms, supporting rapid reconfiguration and vehicle design exploration for future autonomous off-road vehicles such as those used in expeditionary environments.

Expeditionary environments such as disaster zones, forward operating bases, and remote research sites impose severe constraints on manufacturing systems, such as, limited energy availability, environmental contamination, unstable infrastructure, uncertain supply chains, and restricted skilled labor. These constraints are particularly challenging for electronics manufacturing due to its sensitivity to dust, humidity, power instability, and limited in-field verification capability. This paper presents a constraint-aware cellular manufacturing architecture for expeditionary electronics production. A structured requirement translation framework maps environmental and operational constraints into explicit engineering implications for system layout, energy management, and assurance integration. A modular, zone-based cellular architecture is proposed that prioritizes mission-adequate restoration, graceful degradation, and selective energy allocation rather than industrial throughput optimization. A constraint-driven configuration model is introduced to evaluate restoration strategies under bounded time, energy, and quality thresholds. The approach is demonstrated through a representative electronics restoration scenario. The results illustrate how cellular organization supports contamination containment, fault isolation, and operational continuity under expeditionary conditions. The proposed framework provides a systems-level foundation for resilient, field-deployable electronics manufacturing systems.

This study explores the debinding and sintering behavior of copper powder material extrusion (PME) parts with a polylactide (PLA) binder. PME, sometimes known as toolless powder injection molding, is an extrusion-based additive manufacturing (AM) method that produces green parts with high powder loadings (around 90% weight). These parts require debinding and sintering to be useful, similar to those produced by many traditional methods that use powder and binder as their feedstock. A design-of-experiments (DOE) approach was employed to evaluate the effects of different debinding ramp rates, crucible materials, and ballast types. The processing envelope used in the study reflects the simplified, low-complexity debinding and sintering workflow that one of the common features of PME, rather than more complex ones focused on optimizing metallurgy. data showed that the debinding with the alumina ballast produced better mechanical properties, while sintering with a talc ballast at optimized ramp speeds led to greater density and strength of the parts. highest ultimate tensile strength (UTS) achieved was 63.98 MPa with a sintered density of 67.55%. The results outline a realistic performance envelope for copper PME processed under these constraints, both revealing and taking advantage of key tradeoffs between debinding strategy, thermal history, and final part integrity. Microscopy analysis revealed that part quality depended heavily on debinding and sintering conditions, with talc ballast producing more consistent surface integrity for sintered parts.

A methodology for performing Human Operator Modeling (HOM) using a Caterpillar Model 299D3 XE Compact Track Loader (CTL) is presented. The proposed method uses task analysis techniques to decompose material excavation and moving tasks into smaller, individual tasks presented in a task list. A method for verifying and refining the task list is presented, along with a procedure for identifying relevant human operator sensory information and analyzing human decision making in the context of CTL operation. This methodology is then partially verified through the analysis of a non-expert human operator in Vortex Studio, a realistic construction equipment simulator. A modified test course is executed by a non-expert human operator in the simulation environment, and the recorded data is used to create a quantitative Human Operator Model. From this, a Virtual Operator Model (VOM) feedback controller simulating the performance of the human operator is developed. The VOM is implemented using a state machine to transition between individual tasks. Fuzzy Logic Control (FLC), is implemented for each task to control bucket tilt, arm lift, and throttle, with controller parameters calculated from the quantitative HOM data. The VOM controller is verified using the same test course performed by the human operator. The performance of the human operator is compared to that of the VOM controller in order to validate the HOM and VOM methodology for a simulation environment.

This study investigates how feedstock sources and printing parameters influence the tensile properties of polylactide (PLA) produced by fused filament fabrication (FFF), with special attention to differences between virgin and recycled feedstocks. A full factorial experimental design examined 12 factor combination groups created by varying the recycled status of the feedstock, nozzle diameter, and infill raster angle. 72 microtensile specimens were fabricated and tested in accordance with ASTM D1708 at two crosshead speeds. Tensile strength, elongation at break, Young's modulus, Shore D hardness, and density were recorded for each specimen. Analysis of variance (ANOVA) revealed that feedstock recycled status and nozzle diameter significantly affected UTS at both testing speeds, demonstrating that these parameter-to-property trends are robust across strain rates. Elongation at break showed significant effects only at the slower testing speed, indicating strain rate sensitivity. Young's Modulus values were slightly lower at the slower speed, though valid moduli could not be obtained for twice-recycled samples tested at the faster speed. The factorial design also revealed several significant two- and three-way interactions. Overall, recycled feedstock, nozzle geometry, and infill orientation each measurably influence tensile behavior, yet recycled PLA can still provide reliable mechanical performance when key printing parameters are controlled.

Reversible mechanical interlocking is widely used in fastening and attachment systems, yet polymer-based interlocks typically suffer from irreversible deformation and progressive loss of load-bearing capacity under repeated use. This work presents a 4D-printed laminate architecture that integrates stiff shape-memory polylactic acid (PLA) with compliant thermoplastic polyurethane (TPU) to enable recoverable, fatigue-resistant interlocking interfaces. By spatially organizing the two polymers into a controlled sandwich architecture, shape-memory functionality is decoupled from the stiffness of PLA and ductility of TPU, allowing mechanical performance and recoverability to be independently tuned. The thermomechanical response of the laminates was characterized under cyclic programming and recovery at two activation temperatures. Programming near the glass transition temperature resulted in architecture-dependent recovery stability, whereas activation near the cold-crystallization regime produced uniformly high shape fixity and high recoverability across all laminates. When implemented in bio-inspired hook geometries, the optimized laminates exhibited improved cyclic interlocking performance compared to monolithic PLA. While single-hook designs remained susceptible to fatigue due to stress localization, a double-hook geometry distributed load more effectively, suppressed interfacial delamination, and preserved both force and energy dissipation under repeated cycling with thermal recovery. These results establish a material and architecture framework for reusable, shape memory-enabled interlocking systems fabricated via multi-material additive manufacturing.

Fused filament fabrication (FFF) has gained popularity in recent years because it can produce prototypes and functional components with complex geometry. Because of inherent process variability, the components often exhibit defects such as warping, layer delamination, voids, and poor surface finish, as well as issues related to variable material strength and anisotropy. In-situ monitoring (ISM) of the FFF process is a promising technique to predict part performance, which in turn can support accept or reject decisions for printed parts. This paper proposes a framework for incorporating ISM-generated information, with a particular focus on infrared (IR) image analysis for this purpose. IR camera images, in conjunction with numerical features such as infill pattern and extruder nozzle temperature, serve as an input to a multimodal deep learning (MDL) model that predicts the mechanical performance of printed parts. In the framework, convolutional neural nets process image inputs, while a fully connected neural network extracts patterns from numerical process parameters. Furthermore, the proposed approach incorporates an ablation study and Cohort Shapley analysis to identify the most informative monitoring modalities and process parameters. This fusion of modalities enables more accurate and robust prediction of mechanical response than a single-source model. We demonstrate the framework on FFF-printed beams subjected to torque and three point bending tests, and discuss opportunities for future work in vehicle manufacturing and expeditionary sustainment.

This article explored the spiral development process, sometimes called “evolutionary acquisition” in military sectors, and reviewed major non‐software applications in the engineering literature. The spiral development process was originally developed for the design of software while minimizing and managing risk, but the principles can be applied to a wide variety of systems engineering problems where risk management is a priority. The major application domains discussed in this review were product design and development, robotics, agriculture and construction systems, product‐service and human‐technology systems, medical systems and devices, military and aerospace systems, and data management, enterprise systems, and information technology systems. This exploration and accompanying discussion are useful for system designers, systems engineering educators, and other major stakeholders, as it shows successful applications in a wide variety of non‐software technology sectors and provides guidance for application in new areas. The review clearly showed the usefulness and wide variety of non‐software product and system design applications in which the spiral method had been employed from the early 1990s until the present time. Far from being an obsolete or “dated” design method, it has become even more widely used and refined in recent years, which is a trend that appears likely to continue as engineering systems and technology development become more complex and distributed.

Fused filament fabrication (FFF) is a widely used additive manufacturing technique. Several printing parameters, including the print speed and print (extrusion) temperature, influence the properties of the 3D printed material. For instance, reducing print speed and increasing print temperature can improve the material's fracture strength, but they also result in longer print times and higher energy consumption. Optimizing these parameters is essential to achieve a balance between material performance and manufacturing efficiency. However, determining the optimal parameters remains a challenge. Current methods often rely on complex thermal histories of the deposited material to predict the fracture strength of 3D printed polymers, which can be time-consuming and imprecise. To address this challenge, we propose a novel equation derived from polymer healing theory to predict the fracture strength of thermoplastic polymers manufactured via FFF for given print speeds and print temperatures. The material constants in the derived equation were found experimentally using three-point bending experiments for acrylonitrile butadiene styrene (ABS) to validate the equation. Infrared thermography and microcomputed tomography were employed to analyze the underlying assumptions. The findings demonstrate that the proposed equation accurately predicts the fracture strength within the conventionally accepted 90% precision. The proposed equation reduces the reliance on time-consuming simulations and costly experimental testing. It also enables rapid evaluation of trade-offs between print speed, print temperature, mechanical performance, and other factors like print time, energy consumption, and dimensional accuracy, accelerating decision-making, and enhancing process efficiency.

As stepper motors become more and more widely used in engineering systems (vehicles, 3-D printers, manufacturing tools, and similar), the effects of their induced magnetic fields present a concern during the packing and orientation of components within the system. For applications requiring security, this is also a concern as the background electromagnetic radiation (EMF) can be captured at a distance and used to reproduce the motion of the motor during operation. One proposed alternative is to use customized non-magnetic plastic shields created using additive manufacturing. Some small studies have been completed which show some effectiveness of this approach but these studies have been small-scale and difficult to reproduce. To seek a more rigorous answer to this question and collect reproducible data, the present study used full factorial design of experiments with several replications. Three materials were used: Polylactide (PLA), PLA with 25% (weight) copper powder, and PLA with 15% chopped carbon fibers. The factors of interest were infill pattern (gyroid, octet, and concentric) and shield wall thickness (10mm, 20mm, and 30mm), while the response used was strength of magnetic field at two distances (100mm and 200mm) from the motor at various angles. A total of 27 different shield designs were manufactured and tested, with a total of 1176 tests being completed. The results showed some effect, both in shielding and in increasing the magnitude of the EMF, but the effect was significantly smaller than what was shown in some previous screening studies suggesting that some previous studies had a lot of noise in the data. The replications showed excellent consistency, showing that the results are reliable. It was concluded that additively manufactured stepper motor shielding can be used effectively in some cases but is likely not the best shielding option for many scenarios in vehicles and similar applications.

Reliable off-road autonomy requires operational constraints so that behavior stays predictable and safe when soil strength is uncertain. This paper presents a runtime assurance safety monitor that collaborates with any planner and uses a Bekker-based cost model with bounded uncertainty. The monitor builds an upper confidence traversal cost from a lightweight pressure sinkage model identified in field tests and checks each planned motion against two limits: maximum sinkage and rollover margin. If the risk of crossing either limit is too high, the monitor switches to a certified fallback that reduces vehicle speed, increases standoff from soft ground, or stops on firmer soil. This separation lets the planner focus on efficiency while the monitor keeps the vehicle within clear safety limits on board. Wheel geometry, wheel load estimate, and a soil raster serve as inputs, which tie safety directly to vehicle design and let the monitor set clear limits on speed, curvature, and stopping at run time. The method carries uncertainty analytically into the upper confidence cost and applies simple intervention rules. Tuning of the sinkage limit, rollover margin, and risk window trades efficiency for caution while keeping the monitor light enough for embedded processors. Results from a simulation environment spanning loam to sand include intervention rates, violation probability, and path efficiency relative to the nominal plan, and a benchtop static loading check provides initial empirical validation.

The ability to manufacture spare parts, complete repairs, and carry out other important manufacturing activities is a major concern for users in expeditionary environments (battlefields, remote research stations, or disaster relief areas). The challenges that arise include a limited source of energy, security concerns, an unreliable supply chain, poor local infrastructure, harsh weather, and urgency not typically encountered in regular manufacturing environments. This article developed a conceptual model for the challenges encountered in expeditionary manufacturing, with a focus on applications that use robotic systems to complete or assist in the fabrication. A case study was completed to demonstrate the concepts for a realistic scenario. This work is useful for designers and system planners who wish to use robotic systems (including CNC machines and 3D printers) to support manufacturing activities within an expeditionary environment.

This project explored the manufacturability-driven design of mandibular reconstruction implant models made using extrusion-based additive manufacturing. A formalized multi-objective optimization framework was presented for the identification, collection, and mapping of the manufacturability constraints in the design model. This workflow ensures the manufacturability of the final product while also optimizing factors related to geometry, fit, structural integrity, material usage, and biocompatibility. This framework captured the realistic requirements driven by manufacturing processes to ensure that the final design could be manufactured. The method was demonstrated using a detailed case study that included the manufacturing and analysis of the final components and validation of the design, which clearly showed both the opportunities and limitations of engineering plastics for models. The case study results showed design success related to manufacturing, fit, material utility, and biocompatibility, but it was clear that the plastic models were not able to be used directly due to structural concerns. However, they proved to be excellent form/fit prototypes or casting forms for metal or ceramic implants. Common commercial software tools (Materialise Mimics, Autodesk Meshmixer, and nTop) were used throughout the process, making the method more accessible to practical users. This validated methodology will be useful both in the computer-aided design (CAD) and in medical device domains, as it allows the direct application of design-for-additive manufacturing principles during the design of custom implants. Unlike previous works, this design framework integrates manufacturability and performance constraints simultaneously.

Most thermoplastic manufacturing processes, that do not include cutting, involves the melting and re-solidification of the raw material, which results in delamination, warpage, and shrinkage. These undesirable artifacts are introduced due to the build-up of residual stress during fabrication of the part. They not only affect the process reliability and repeatability, but also the service life and aesthetics of the final product. This is of particular concern in extrusion-based additive manufacturing of thermoplastics with relatively high melting temperatures, such as polycarbonate (PC). By controlling the process parameters, a certain degree of influence can be maintained on the multiple heating/cooling cycles and the corresponding phase transformations that induce differential shrinkage in the part. In the current study, the influence of the orientation of the fabricated part (flat and horizontal11 In the case of a plate, assuming that the nozzle prints in the x–y plane, the flat orientation is when the height is aligned along the z-direction and the horizontal orientation is when the width is aligned along the z-direction.) on the process history, and as a result on the residual stress distribution in rectangular plates printed using fused filament fabrication (FFF) is studied. This work used a thermodynamically-consistent model previously derived for extrusion-based additive manufacturing to run simulations within ABAQUS. Corresponding experiments were conducted to validate the model, along with the error and repeatability analysis. The final dimensions of the plates measured from the experiments matched exceptionally well with the values measured from the simulations. The simulations predicted that the residual stress distribution in each orientation is extremely different. It mainly depended on the distribution of the weight fraction of the glass phase and temperature, which have significantly distinct patterns in both orientations. The simulation also predicted very different possible failure regions for the plates printed in the flat and horizontal orientations.

Large-scale extrusion-based concrete printing systems have become an excellent option for autonomously completing construction activities in expeditionary environments. These environments typically are in war zones, disaster areas, remote research stations, and other conditions where energy may be scarce, there may be security risks, and where the job may be too dangerous or difficult for human workers due to environmental or weather conditions. The article develops and presents a system design and architecture for these systems, where a team of printing robots do the construction activities and are resupplied by tenders. All vehicles must recharge their batteries periodically. This article presented a full system-level design model for implementing the system in the field, with the mapped hardware, software, and communication interfaces. Functional requirements and a concept of operations (CONOPS) diagram were also developed to represent the system. A detailed case study was done and analyzed, demonstrating the value of the system design method for putting a real system to work in an expeditionary environment. This work will be helpful in the further development, refinement, and application of this and similar systems by showing the main architecture of the system and formalizing the requirements for developing the system. This system architecture is only part of a larger possible system design for autonomous construction, which may include other construction vehicles, UAVs, and sophisticated control and localization systems.