Local Behavior Research Articles

Service quality facets and hotel customer retention in Ghana: Evidence from the Volta Region

Service quality and customer retention remain essential issues in the service sector. This research delves into unravelling the complex relationships between the facets of the SERVQUAL model (reliability, responsiveness, tangibility, assurance, and empathy) and the retention of hotel customers in less-urban areas of Ghana. A cross-sectional survey of 450 customers of hotels in the Volta Region produced data for descriptive and regression analyses using Smart PLS 4. The results show that service quality was rated moderately, only assurance and empathy significantly affect customer retention, while tangibility, reliability, and responsiveness do not. Generalizability of our findings to other regions of Ghana and elsewhere might be questioned because the study was limited to only one region. However, this seeming limitation provides novelty and value in several ways. Firstly, while SERVQUAL is widely used, its application to less-urban geographical areas like the Volta Region is uncommon. Moreover, the study provides a deeper understanding of how service quality affects customer retention by focusing on a specific, narrow regional area. Further, by differing from the usual broader hospitality research, this distinctive approach offers valuable insights into local customers' unique preferences and behaviours that larger-scale studies may overlook.

Predicting edge fracture in dual-phase steels: Significance of anisotropy-induced localization

While experimental methods for characterizing edge fracture have advanced significantly, current modeling approaches often neglect factors like anisotropy evolution and localization, limiting their ability to accurately predict edge fracture across various tests. In the present study, we investigate the anisotropic deformation, localization, and fracture behavior of a dual-phase (DP1000) steel during hole expansion tests using an advanced evolving anisotropic model coupled with a hybrid damage mechanics model. The anisotropic plasticity model is calibrated by tensile tests along different loading directions and is capable of describing both anisotropic hardening and r-value evolution, while the fracture model is calibrated by tests under several stress states. To illustrate the impact of anisotropy, an isotropic version of the model is also included for comparison. The novelty of the investigation is that it originally found the edge fracture of the DP1000 steel is anisotropic and triggered by through-thickness localization induced by material anisotropy. Therefore, only the model with anisotropy can provide a satisfactory prediction of the hole expansion ratio as well as the location of the edge fracture, while the isotropic model overestimates the experiments significantly. The findings provide an in-depth understanding of the importance of anisotropy in evaluating edge fracture behavior, which not only improves the modeling accuracy but also adds a design concept to enhance the edge formability of materials.

Linking the microstructure with strain-life curves for improved utilization of the lightweight potential of thick-walled nodular cast iron

The assessment of the fatigue life of critical, highly stressed component areas is an important aspect in the design of thick-walled components for wind turbines made of nodular cast iron. With the demand for resource efficiency through lightweight design combined with a certain capability to withstand extreme loads and special events, this issue is becoming increasingly important. However, there are still gaps in the description of local strain-based material behaviour. For the design and local strain-based fatigue assessment of large cast components, possibilities to determine the fatigue life as accurately as possible must be provided by standards and guidelines. The paper aims to provide a wide range of material and fatigue data from one common source for general design interests. During research projects at Fraunhofer LBF, material properties for the PRAM-based fatigue life assessment and the elastic-plastic material behaviour have been derived from 9 nodular cast iron grades with 44 microstructural variations. To describe the influence of the technological size effect on cyclic stress-strain and PRAM-N curves the quasi-static parameters (tensile strength and elongation at break) and the microstructure (nodularity and graphite particle density) are considered. In addition, suggestions for scatter bands in the strain-based design approach are given to the designers of thick-walled GJS components.

Influence of magnetic field-dependent viscosity on Casson-based nanofluid boundary layers: A comprehensive analysis using Lie group and spectral quasi-linearization method

This study examines the effects of magnetic-field-dependent (MFD) viscosity on the boundary layer flow of a non-Newtonian sodium alginate-based Fe3O4 nanofluid over an impermeable stretching surface. The non-Newtonian Casson and homogeneous nanofluid models are utilized to derive the governing flow and heat transfer equations. Applying Lie group transformations to dimensional partial differential equations yields nondimensional ordinary differential equations, which are then numerically solved using the spectral quasi-linearization technique. The analysis primarily focuses on the impacts of the MFD viscosity parameter, nanoparticle volume fraction of Fe3O4, and magnetic parameters on the flow and heat transfer characteristics. The local skin friction and heat transfer rate behaviors influenced by viscosity changes due to the magnetic field are discussed. It is found that MFD viscosity significantly impacts flow and thermal energies, enhancing skin friction coefficients and reducing Nusselt numbers in the boundary layer region.

Numerical simulation for non-uniform PtCo catalyst degradation under different coolant conditions and its effect on PEMFC performance

Long-term non-uniform temperature, pressure and reaction rates distributions in the proton exchange membrane fuel cells (PEMFCs) may result in local catalyst degradation and deteriorate PEMFC performance. However, the problem of non-uniform catalyst degradation in PEMFC stacks is still incompletely understood due to the lacking of advanced experimental methods and three-dimensional (3D) catalyst aging models. In this study, a 3D PtCo alloy catalyst degradation model under voltage cycles is built and a 25 cm2 PEMFC stack containing realistic cathode, anode as well as coolant flow fields is used as the computational domain to analyze in detail the influence of non-uniform catalyst degradation on the performance of the PEMFC during different coolant conditions. The simulation results show that the non-uniform catalyst degradation is strongly dependent on the cathode flow field structure. It can alleviate non-uniform catalyst degradation as well as contribute to improving PEMFC performance when the coolant flow direction is the same as the air, and both coolant flow rate and inlet temperature also are found to significantly affect the local catalyst degradation behavior. Therefore, an optimally designed cathode flow fields structure as well as good water and heat management during operation can help to extend the service life of the PEMFC.

Computation of Normal Form and Unfolding of Codimension-3 Zero-Hopf–Hopf Bifurcation

The computation of the normal form as well as its unfolding is a key step to understand the topological structure of a bifurcation. Though a lot of results have been obtained, it still remains unsolved for higher co-dimensional bifurcations. The main purpose of this paper is devoted to the computation of a codimension-3 zero-Hopf–Hopf bifurcation, at which a zero as well as two pairs of pure imaginary eigenvalues can be found from the matrix evaluated at the equilibrium point. Different distributions of eigenvalues are considered, which may behave in a non-semisimple form for 1:1 internal resonance. Based on the combination of center manifold and normal form theory, all the coefficients of normal forms and nonlinear transformations are derived explicitly in terms of parameters of the original vector field, which are obtained via a recursive procedure. Accordingly, a user friendly computer program using a symbolic computation language Maple is developed to compute the coefficients up to an arbitrary order for a specific vector field with zero-Hopf–Hopf bifurcation. Furthermore, universal unfolding parameters are derived in terms of the perturbation of physical parameters, which can be employed to investigate the local behaviors in the neighborhood of the bifurcation point. Here, we emphasize that though different norm forms based on different choices may exist, their topological structures are the same, corresponding to qualitatively equivalent dynamics.

Local resetting in non-conserving zero-range processes with extensive rates

A non-conserving zero-range process with extensive creation, annihilation and hopping rates is subjected to local resetting. The model is formulated on a large, fully-connected network of states. The states are equipped with a (bounded) fitness level: particles are added to each state at a rate proportional to the fitness level of the state. Moreover, particles are annihilated at a constant rate, and hop at a fixed rate to a uniformly-drawn state in the network. This model has been interpreted in terms of population dynamics: the fitness is the reproductive fitness in a haploid population, and the hopping process models mutation. It has also been interpreted as a model of network growth with a fixed set of nodes (in which particles occupying a state are interpreted as links pointing to this state). In the absence of resetting, the model is known to reach a steady state, which in a certain limit may exhibit a condensate at maximum fitness. If the model is subjected to global resetting by annihilating all particles at Poisson-distributed times, there is no condensation in the steady state. If the system is subjected to local resetting, the occupation numbers of each state are reset to zero at independent random times. These times are distributed according to a Poisson process whose rate (the resetting rate) depends on the fitness. We derive the evolution equation satisfied by the probability law of the occupation numbers. We calculate the average occupation numbers in the steady state. The existence of a condensate is found to depend on the local behavior of the resetting rate at maximum fitness: if the resetting rate vanishes at least linearly at high fitness, a condensate appears at maximum fitness in the limit where the sum of the annihilation and hopping rates is equal to the maximum fitness.

Geotechnical analysis involving strain localization of overconsolidated soils based on unified hardening model with hardening variable updated by a composite scheme

AbstractStrain localization simulation of overconsolidated soils with high overconsolidation ratio (OCR) has been a long‐standing challenge. Some critical state soil models, including the modified Cam‐clay (MCC) model, have been widely applied, but they may not predict the shear dilatancy of overconsolidated soils well in some cases. Hence, the unified hardening (UH) model, which may be viewed as a generalized version of the MCC model, is implemented. It has been recognized, nonetheless, that without resorting to the regularization mechanism, the standard finite element method (FEM) or the second‐order cone programming optimized finite element method (FEM‐SOCP) often experiences instability or interruption of calculating the hardening‐softening responses of overconsolidated soils. To resolve the aforementioned difficulty, the UH model is developed and implemented in the framework of FEM‐SOCP based on the micropolar continuum (mpcFEM‐SOCP) to predict strain localizations of overconsolidated soils. Furthermore, to obviate non‐convexity of mpcFEM‐SOCP induced by material softening, an effective composite update scheme of hardening variable pc, which refers to the implicit variable (IV) scheme for the hardening stage and then refers to the explicit variable (EV) scheme for the softening stage, is proposed. Based on one biaxial compression problem and one rigid strip footing problem, numerical analyses disclose that by applying mpcFEM‐SOCP in conjunction with the composite update scheme of pc, the UH model of micropolar continuum can effectively predict the strain localization behavior of overconsolidated soil during its failure stage, and the stable hardening‐softening responses of overconsolidated soils can be readily attained.

Comparative analysis of nanoindentation-induced incipient deformation of zirconium-based bulk metallic glass in various structural states

The incipient plastic deformation behaviour of as-cast and annealed samples of Zr50Cu40Al10 (atom %) bulk metallic glass was investigated by nanoindentation. A validated load-over-displacement versus displacement plot showed the existence of a precursor event to incipient plasticity in both samples. The activation stress remained consistent in both samples, indicating that the event corresponds to local behaviour in regions with the same energy state, and it is not influenced by the overall microstructure. Conversely, the first serration detected in the as-relaxed sample exhibited a greater magnitude, potentially arising from a distinct energy-dissipation rate related to larger-scale microstructural characteristics.

Seismic Retrofitting of Existing Reinforced Concrete Buildings Using Aluminium Shear Links and Eccentric Steel Chevron Braces

Many existing reinforced concrete buildings have been designed based on earlier codes of practice that underestimated seismic forces, making them vulnerable to damage during seismic action. Equipping existing buildings with shear links and eccentric braces is one of the available seismic retrofitting methods to dissipate seismic energy away from the main structural members. In this paper, a proposal for the seismic retrofitting of two existing reinforced concrete buildings using aluminium shear links and steel braces is presented. First, a capacity-based design approach is followed to determine the required sizes of the shear links and eccentric braces. Second, numerical analyses are used to compare how the original and retrofitted buildings responded. These tests include pushover analysis, nonlinear time-history analysis, damage analysis, incremental dynamic analysis, fragility and reliability analysis, and damage analysis. The results reveal that the proposed retrofitting method can sufficiently upgrade the performance level of the buildings and reduce their storey displacements and interstorey drifts, as shear links are found to absorb almost all seismic energy, therefore keeping other structural members responding elastically. Yet, using shear links alters the local behaviour of the surrounding structural members, which should be considered in the design process. Furthermore, compared to the original buildings, retrofitted buildings are expected to undergo less structural damage as they have lower damage indices. Meanwhile, the fragility of retrofitted buildings is significantly reduced compared to the original ones, which indicates the efficiency of the proposed retrofitting methods in upgrading the performance of seismically deficient reinforced concrete buildings.

On the singular limit problem in nonlocal balance laws: Applications to nonlocal lane-changing traffic flow models

We present a convergence result from nonlocal to local behavior for a system of nonlocal balance laws. The velocity field of the underlying conservation laws is diagonal. In contrast, the coupling to the remaining balance laws involves a nonlinear right-hand side that depends on the solution, nonlocal term, and other factors. The nonlocal operator integrates the density around a specific spatial point, which introduces nonlocality into the problem. Inspired by multi-lane traffic flow modeling and lane-changing, the nonlocal kernel is discontinuous and only looks downstream. In this paper, we prove the convergence of the system to the local entropy solutions when the nonlocal operator (chosen to be of an exponential type for simplicity) converges to a Dirac distribution. Numerical illustrations that support the main results are also presented.

How far are cities from the x-minute city vision? Examining current local travel behavior and land use patterns in Montreal, Canada

In the past three years the 15-minute city planning concept has captured the attention of policy makers and the public worldwide. Some regions have included it in their planning goals and others modified it to 30 min to make it more attainable in their local context. The goal of this research is to measure whether the 15- or 30-minute city goals align with current travel behaviour and land use patterns in the North American context using Montreal, Canada as the case study. In doing so, we look at which destinations are cultivating local travel patterns consistent with the 15- and 30-minute city concepts and identify any unique qualities of these areas using the 2018 Montreal origin-destination travel diaries. Our bivariate analysis finds very few destinations in Montreal where a high number of trips and high percentage of trips are ending using a sustainable mode of transport and below the 15- or 30-minute travel time threshold. We further investigate the land use patterns that align with the 15- and 30-minute city to recommend realistic planning goals and policy interventions that match the North American context. The findings from this research can be of interest to transport professionals and policy makers trying to implement the 15- or 30- minute city concepts to their regions.

A multi-scale tracking approach for conserving large migratory fish in an open coastal environment

Coastal habitats serve essential roles in the life cycles of migratory fishes, impacting both local and regional population stability. Conservation efforts for coastal fish often rely on spatial approaches within designated boundaries to mitigate threats and enhance production. However, in open coastal environments, migratory behaviours can extend beyond these protected areas, exposing individuals to potential threats or population bottlenecks elsewhere in their range. To improve conservation outcomes, a comprehensive understanding of movements across the entire migratory range is essential. Aquatic telemetry is a valuable tool for studying these behaviours, but must be adapted to address questions at multiple spatial and temporal scales. In this study we demonstrate how a combination of telemetry techniques can capture both local and regional fish behaviours. We begin by introducing the implications of migratory behaviours for fish conservation in open coastal environments, using the Wadden Sea as an example where additional research and management are needed to address fish declines. We then present a case study which uses the Dutch Wadden Sea to illustrate how a multi-scale telemetry approach can enhance both fundamental knowledge and conservation strategies for migratory fish. Within this case study, we present the general movement strategies exhibited by coastal migrants, alongside an overview of telemetry techniques applicable for open coastal systems. We then apply a size-based assessment using a reference tag to estimate the suitability of common Wadden Sea species for long-term tracking. Drawing from these results, we select four example species to showcase how species-specific understanding of fish life history and abundance can guide tracking studies, accompanied by illustrative examples using telemetry data. Expanding from this case study, we transition to a broader discussion were we provide overarching perspectives on tracking in open coastal ecosystems and offer recommendations to enhance future tracking studies in the Wadden Sea. The integration of telemetry methodologies aligns research and management with fish movement over multiple scales, improving our understanding of fish behaviors and contributing to more effective conservation strategies.

Inverse design of pore wall chemistry and topology through active learning of surface group interactions.

Design of next-generation membranes requires a nanoscopic understanding of the effect of biologically inspired heterogeneous surface chemistries and topologies (roughness) on local water and solute behavior. In particular, the rejection of small, neutral solutes, such as boric acid, poses a heretofore unsolved challenge. In prior work, a computational inverse design technique using an evolutionary optimization successfully uncovered new surface design strategies for optimized transport of water over solutes in smooth, model pores consisting of two surface chemistries. However, extending such an approach to more complex (and realistic) scenarios involving many surface chemistries as well as surface roughness is challenging due to the expanded design space. In this work, we develop a new approach that uses active learning to optimize in a reduced feature space of surface group interactions, finding parameters that lead to their assembly into ordered, optimal patterns. This approach rapidly identifies novel surface functionalizations that maximize the difference in water and boric acid transport through the nanopore. Moreover, we find that the roughness of the nanopore wall, independent of its chemistry, can be leveraged to enhance transport selectivity: oscillations in the pore wall diameter optimally inhibit boric acid transport by creating energetic wells from which the solute must escape to transport down the pore. This proof-of-concept demonstrates the potential for active learning strategies, in concert with molecular simulations, to rapidly navigate complex design spaces of aqueous interfaces and is promising as a tool for engineering water-mediated surface interactions for a broad range of applications.

An innovative Fibonacci wavelet collocation method for the numerical approximation of Emden-Fowler equations

This article presents a novel approach using the Fibonacci wavelet collocation method (FWCM) for the numerical solution of Emden-Fowler-type equations. The Emden-Fowler equations are a class of nonlinear differential equations that arise in various fields of science and engineering, particularly in astrophysics and fluid dynamics. Due to their nonlinear and singular nature, the conventional approaches to solving these equations encounter difficulties. This method is particularly effective in handling problems with singularities, as it adapts naturally to the local behaviour of the solution. Here, we introduced the Fibonacci wavelet collocation method as a powerful numerical technique for tackling Emden-Fowler-type equations. The Fibonacci wavelet basis functions possess remarkable properties, including compact support, making them well-suited for approximating solutions to differential equations. The main advantage of this approach lies in its ability to reduce the computational complexity associated with solving Emden-Fowler equations, resulting in accurate and efficient solutions. Comparative analyses with other established numerical methods reveal its superior accuracy and convergence rate performance. Further, several examples demonstrate the method's flexibility when dealing with different singularity levels. This paper contributes to numerical analysis by introducing the Fibonacci wavelet method as a robust tool for solving Emden-Fowler-type equations.

G–LIME: Statistical Learning for Local Interpretations of Deep Neural Networks Using Global Priors (Abstract Reprint)

To explain the prediction result of a Deep Neural Network (DNN) model based on a given sample, LIME [1] and its derivatives have been proposed to approximate the local behavior of the DNN model around the data point via linear surrogates. Though these algorithms interpret the DNN by finding the key features used for classification, the random interpolations used by LIME would perturb the explanation result and cause the instability and inconsistency between repetitions of LIME computations. To tackle this issue, we propose G-LIME that extends the vanilla LIME through high-dimensional Bayesian linear regression using the sparsity and informative global priors. Specifically, with a dataset representing the population of samples (e.g., the training set), G-LIME first pursues the global explanation of the DNN model using the whole dataset. Then, with a new data point, -LIME incorporates an modified estimator of ElasticNet-alike to refine the local explanation result through balancing the distance to the global explanation and the sparsity/feature selection in the explanation. Finally, G-LIME uses Least Angle Regression (LARS) and retrieves the solution path of a modified ElasticNet under varying -regularization, to screen and rank the importance of features [2] as the explanation result. Through extensive experiments on real world tasks, we show that the proposed method yields more stable, consistent, and accurate results compared to LIME.

Membrane Catalyzed Formation of Nucleotide Clusters and Their Role in the Origins of Life: Insights from Molecular Simulations and Lattice Modeling.

One of the mysteries in studying the molecular "Origin of Life" is the emergence of RNA and RNA-based life forms, where nonenzymatic polymerization of nucleotides is a crucial hypothesis in formation of large RNA chains. The nonenzymatic polymerization can be mediated by various environmental settings, such as cycles of hydration and dehydration, temperature variations, and proximity to a variety of organizing matrices, such as clay, salt, fatty acids, lipid membrane, and mineral surface. In this work, we explore the influence of different phases of the lipid membrane toward nucleotide organization and polymerization in a simulated prebiotic setting. Our molecular simulations quantify the localization propensity of a mononucleotide, uridine monophosphate (UMP), in distinct membrane settings. We perform all-atom molecular dynamics (MD) simulations to estimate the role of the monophasic and biphasic membranes in modifying the behavior of UMPs localization and their clustering mechanism. Based on the interaction energy of mononucleotides with the membrane and their diffusion profile from our MD calculations, we developed a lattice-based model to explore the thermodynamic limits of the observations made from the MD simulations. The mathematical model substantiates our hypothesis that the lipid layers can act as unique substrates for "catalyzing" polymerization of mononucleotides due to the inherent spatiotemporal heterogeneity and phase change behavior.

In vivo evaluation of a Nano-enabled therapeutic vitreous substitute for the precise delivery of triamcinolone to the posterior segment of the eye

This study focused on the design of a thermoresponsive, nano-enabled vitreous substitute for the treatment of retinal diseases. Synthesis of a hydrogel composed of hyaluronic acid and a poloxamer blend was undertaken. Poly(D,L-lactide-co-glycolide) acid nanoparticles encapsulating triamcinolone acetonide (TA) were synthesised with a spherical morphology and mean diameter of ~ 153 nm. Hydrogel fabrication and nanoparticle loading within the hydrogel was confirmed via physicochemical analysis. Gelation studies indicated that hydrogels formed in nine minutes and 10 min for the unloaded and nanoparticle-loaded hydrogels, respectively. The hydrogels displayed in situ gel formation properties, and rheometric viscoelastic studies indicated the unloaded and loaded hydrogels to have modulus values similar to those of the natural vitreous at 37 °C. Administration of the hydrogels was possible via 26G needles allowing for clinical application and drug release of triamcinolone acetonide from the nanoparticle-loaded hydrogel, which provided sustained in vitro drug release over nine weeks. The hydrogels displayed minimal swelling, reaching equilibrium swelling within 12 h for the unloaded hydrogel, and eight hours for the nanoparticle-loaded hydrogel. Biodegradation in simulated vitreous humour with lysozyme showed < 20% degradation within nine weeks. Biocompatibility of both unloaded and loaded hydrogels was shown with mouse fibroblast and human retinal pigment epithelium cell lines. Lastly, a pilot in vivo study in a New Zealand White rabbit model displayed minimal toxicity with precise, localised drug release behaviour, and ocular TA levels maintained within the therapeutic window for the 28-day investigation period, which supports the potential applicability of the unloaded and nanoparticle-loaded hydrogels as vitreous substitutes that function as drug delivery systems following vitrectomy surgery.Graphical Fig. aSchematic representation of the nano-enabled therapeutic vitreous substitute synthesis process. This figure was partly generated using Servier Medical Art, provided by Servier, licensed under a Creative Commons Attribution 3.0 unported license

Abstract 4272: Disruption of hyaluronan metabolism alters glioma cell proliferation by ligand dependent and independent mechanisms

Abstract Hyaluronan (HA) is the main constituent of the brain extracellular matrix and is an essential component of the glioblastoma (GBM) tumor microenvironment. The biosynthesis and catabolism of hyaluronan has multiple roles in tissue architecture and cell signaling. Dysregulation of these mechanisms is crucial in pathological processes such as cancer, inflammation or tissue remodeling. The role of HA is believed to be strongly dependent on its size (molecular weight), location, and cell receptor density and activity. HA is produced intracellularly by HA synthases (HAS1-3) and can also be catabolized endogenously by hyaluronidases (HYAL1-3).The fabrication of controlled microenvironments provided by three dimensional (3D) models helps to elucidate the role of HA signaling in GBM tumors. We exploit here the advantages of these models to understand the role of hyaluronan in the local behavior of GBM after radiation therapy and selected targeted inhibitors. We have established engineered brain tumor biomaterials based on functionalized hydrogels to monitor the response of patient-derived xenograft cell populations with different molecular signatures in combination with microfluidic devices. We have analyzed shifts in metabolism, hyaluronan secretion, as well as hyaluronan synthetic enzymes (HAS) and hyaluronidases (HYAL) activity in an array of patient derived GBM cells. We reveal that endogenous HA plays a role in mitochondrial respiration and cell proliferation in a tumor subtype dependent manner. We also show that HA fragments can enhance tumor metabolism and growth through ligand dependent and independent mechanisms. We provide bioengineered platforms and strategies to predict and stratify tumors in order to achieve more efficient combinatorial treatments targeting endogenous hyaluronan production. This work emphasizes the potential of these preclinical models to predict and accelerate cancer treatments, more relevant in malignancies with limited treatment options. Citation Format: Edward R. Neves, Joseph Mueller, Achal Anand, Kimberly Selting, Hui Xu, Roddel Remy, Brendan Harley, Sara Pedron-Haba. Disruption of hyaluronan metabolism alters glioma cell proliferation by ligand dependent and independent mechanisms [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4272.

Influence of Complex Geometries on Damage Tolerance of Porous Carbon Fiber Network

Porous materials exhibit a variety of attractive functional properties for aerospace applications, such as low density and low thermal conductivity. However, they must also be mechanically robust and damage tolerant to fully realize their potential. Currently, it is costly and time-consuming for testing under service conditions, therefore, computational models are a good path forward. Due to the inherent microstructural stochasticity of these structures, however, their behavior is difficult to effectively model without detailed experimental studies for validation and benchmarking. To that end this study investigates the mechanical properties of a porous carbon fiber network and ties together the global macroscopic observations to the local mesoscale behaviors dictated by individual fibers and fiber junctions. Strain localization was observed using digital image correlation (DIC) and tied to features within the macroscopic stress–strain plots. Work to quantify the impact of the addition of complex geometries (e.g., cracks and through-holes) on mechanical reliability was conducted. The defects resulted in distinct macroscale mechanical characteristics and mesoscale deformation behaviors, depending on defect type and loading orientation. These results provide broad experimental data to inform and validate modeling approaches to accurately predict and tailor the reliability of porous parts under service conditions.