Key Locations Research Articles

Experimental and numerical analysis of temperature distributions in SA 387 pressure vessel steel during submerged arc welding

Abstract The present study aims to explore experimental investigations and numerical simulations for temperature distributions at heat-affected zones within SA 387-Gr.11-Cl.2 steel during the submerged arc welding (SAW) process. Experimental endeavors entailed welding steel plates under controlled conditions, precisely measuring temperatures at key locations by thermocouples. A special program based on 3D Goldak’s double ellipsoidal model was developed in ANSYS Parametric Design Language for moving heat source calculations in the finite-element analysis (FEA). For welding an 8 mm thick plate with one pass, the suitable parameters were found to be 600 A current, 31 V voltage, and 10 mm·s−1 welding speed. The experimental cooling periods were found to be slower than predicted by FEA. When temperature distributions were compared between experimental and FEA results, an average variation of 1.88% at peak temperatures and 11.8% at completion time was observed. The results showed the temperature distribution at various time steps, illustrating the transient nature of the welding process. The results highlight the capacity of the FEA model to predict temperature profiles during SAW accurately, presenting a potent tool for optimizing welding parameters without extensive trial and error.

Daily ranging and den usage patterns structure the spatiotemporal properties of social encounters in spotted hyenas

Fission–fusion dynamics describe the tendency for members of some animal societies to associate in subgroups that change size and structure fluidly over time. These dynamics shape social complexity and social structure, but are difficult to study because they unfold simultaneously over large spatial scales. Here we use simultaneous, fine-scale GPS data from spotted hyenas to examine fission–fusion dynamics through a dyadic analysis of merge-split events between pairs of individuals. We introduce a species-agnostic framework for identifying merge-split events and discretizing them into three phases (merging, together, and splitting), enabling analysis of each phase as well as the connections among phases. Applying this framework to the hyena data, we examine the temporal and spatial properties of merges and splits between dyads and test the extent to which social encounters are driven by key locations. Specifically, we focus on communal dens—shelters for juvenile hyenas where classical observational studies often report large aggregations of adults. We find that overall, 62% of merges occurred at communal dens, supporting the idea that dens facilitate meet-ups and subsequent social behavior. Social encounters most commonly involved close approaches within a few meters between hyenas, while co-travel together occurred in only 11% of events. Comparison to permutation-based reference models suggests that independent movement decisions structure broad-scale patterns of social encounters but do not explain the fine-scale dynamics of interactions that unfold during these encounters. We reflect on how physical features such as dens can become social hotspots, causing social and spatial processes to become fundamentally intertwined.

Multi-sensor data fusion reconstruction method for vibration dynamic responses of aerospace structures

The dynamic responses of key locations are important inputs for the life and reliability assessment of spacecraft structures. Due to the limited sensing resources, most critical responses are difficult to measure directly. A structural dynamic response reconstruction method is necessary. The responses of target locations can be reconstructed based on the empirical mode decomposition (EMD) of measured signals and the modal superposition. However, the structural modal information contained in the measured signal of a single sensor is limited, affecting the reconstruction accuracy. In this paper, a response reconstruction method based on multi-sensor data fusion is proposed. It is applied to a main load-bearing structure of a spacecraft and its typical components to verify its strain response reconstruction effect under random vibration loads. The experimental results show that multi-sensor data fusion improves the strain reconstruction accuracy. The maximum reduction in reconstruction error is from 8.7% to 1.3%. The reconstruction accuracy is further improved with the increase in the number of sensors. The optimal weighted fusion strategy for this problem is the weights defined by the Euclidean distance (EUC) or the dynamic time warping distance (DTW). The fusion results show a better performance with the increase in the power of the defined distance. The proposed multi-sensor fusion method improves the reconstruction accuracy via supplementing structural information to each other and eliminating the instability of single measured signals. More accurate dynamic responses via reconstruction reduce the large input uncertainty in life prediction and lay the foundation for building structural digital twins and managing structural health more effectively.

Nature on our doorstep: How do residents perceive urban parks vs. biodiverse areas?

The role of nature in enhancing urban well-being is well-established, but perceived naturalness may not always align with scientific definitions. Our study aimed to investigate whether areas selected for nature-related activities demonstrate increased biodiversity, offer diverse experiences, and integrate both social and ecological perspectives. We aimed to bridge the gap between perceived naturalness and objective ecological richness. Integrating social and environmental parameters, we considered both objective indicators, such as the presence of rare species, and subjective perspectives. Extensive geotagged surveys among 401 working-age Warsaw residents, coupled with field analyses, and biodiversity data collected for the scale of the whole city, allowed to juxtapose human perception with tangible ecological indicators. Our results revealed that only 14% of the locations identified by respondents as natural were associated with high biological diversity. In contrast, over 30% were in areas with low biological diversity, lacking rare species. Factors like presence of natural and semi-natural vegetation types, distance from buildings, population density, presence of water, noise, and extreme temperatures were found to be significant. We distinguished four types of natural areas: close to home, open grassland, high naturalness, and forested, reflecting different preferences and alternative choices when high-quality natural areas are not nearby. Most notably, urban parks emerged as key locations for nature contact, even though objective measures of biodiversity were often low. This underscores the need for a comprehensive understanding of how urban residents interact with and value natural spaces, bridging the gap between subjective experiences and objective ecological richness within the city's green areas. Our study highlights the complex interplay between the physical properties of urban green spaces, individual perceptions, and the ecological aesthetics influencing these interactions. In particular, the concept of perceived naturalness emerges as a critical factor, often contrasting with objective, quantifiable naturalness, and necessitating a nuanced approach in urban planning and public health contexts to cater to diverse needs and preferences of city dwellers.

Development of Pilgrimage Tourism in Slovakia over the Past Decades: Examples of Selected Pilgrimage Sites

Pilgrimage tourism, among the earliest forms of tourism with a tradition spanning centuries, stands as a steadfast global attraction. This article delves into the significance, diversity, and historical roots of this tourism type, recognizing the contemporary surge in interest in pilgrimage sites. Offering an overview of globally prominent pilgrimage destinations and highlighting key locations in Slovakia, the article emphasizes the country’s considerable potential for the utilization and development of these sacred sites, despite its compact size. It stresses the need to foster this historically significant tourism sector and the necessity for attention and support from the government sector to maximize its potential. The relevance of pilgrimage became particularly apparent during the COVID-19 pandemic, with observable visitor participation despite challenging conditions at various pilgrimage sites. The article examines the pilgrimage’s evolution before, during, and after the pandemic, using Levoča and Šaštín in Slovakia as illustrative cases. One of the main objectives of this study was to clarify the development of pilgrimage tourism in Slovakia over the past decades and the factors influencing it. The attendance analysis unmistakably reveals a significant upward trend at these specific locations, emphasizing the need to establish collaborative efforts to support this sector. Such collaboration is crucial for ensuring the sustainability of historically significant sites, fostering local development, and increasing the visibility of less-visited pilgrimage destinations.

Correlates of mental disorder and harmful substance use in an indigenous Australian urban sample: an analysis of data from the Queensland Urban Indigenous Mental Health Survey.

Limited data exists on the relationship between sociodemographic and cultural variables and the prevalence of specific mental and substance use disorders (MSDs) among Indigenous Australians, using diagnostic prevalence data. This paper utilises data from the Queensland Urban Indigenous Mental Health Survey (QUIMHS), a population-level diagnostic mental health survey, to identify socioeconomic and cultural correlates of psychological distress and specific MSDs in an urban Indigenous Australian sample. Using a mixture of household sampling (door-knocking) and snowball sampling (promotion of the survey in the community), 406 participants aged 18 to 89 were recruited across key locations in Southeast Queensland. The study investigated various demographic, socioeconomic, and cultural factors as predictors of psychological distress (measured by the Kessler-5) and MSD diagnoses (utilising the Composite International Diagnostic Interview, CIDI 3.0) using a series of univariate logistic regressions. Individuals in unstable housing (homeless, sleeping rough) and those reporting financial distress were more likely to experience an MSD in the past 12 months and throughout their lifetime. Individuals reporting lower levels of connection and belonging, limited participation in cultural events, and lower empowerment were more likely to have a lifetime mental disorder. This data emphasises the importance of addressing systemic and social determinants of health when designing and delivering community mental health services and underscores the need for holistic approaches when working with Indigenous communities.

Nth-plant scenario for blended pellets of Miscanthus, Switchgrass, and Corn Stover using multi-modal transportation: Biorefineries and depots in the contiguous U.S.

The sustainability of the biofuel industry depends on the development of a mature conversion technology on a national level that can take advantage of the economies of scale: the nth-plant. This study addresses the logistic challenge of mobilizing national cellulosic feedstock supplies for a sustainable bioenergy industry. A Mixed Integer Linear Programming (MILP) model was developed and updated to deliver on-spec biomass that considers both a desired quantity and quality at the biorefinery. Our supply chain analysis includes multi-modal transport (truck and rail), varying depot and biorefinery sizes, and feedstock blends of corn stover (harvested by either a two- or three-pass method), switchgrass, and miscanthus. The following US states: Illinois, Kansas, Missouri, North Carolina, Oklahoma, Georgia, and Texas were identified as key locations for producing accessible miscanthus. Based on our most optimistic scenario, using trucks as the only transportation mode in 2040 with a cost target of $79/dt, corn stover, switchgrass, and miscanthus could help meet 48% of the EPA target, 173 million dry tons that translate into 7.8 billion GGE. The addition of rail transportation for biomass delivery to biorefineries could help meet 79% of the EPA target, 283 million dry tons that translate into 12.7 billion GGE.

Experimental study of concrete-filled stainless steel tubular stub columns with circular and square cross-sections subjected to combined compression and bending

This paper presents an experimental study into the structural behaviour and strength of concrete-filled stainless steel tubular stub columns with circular and square cross-sections subjected to combined compression and bending moment. A total of sixteen concrete-filled stainless steel tubular (CFSST) stub columns were tested, including two section types (circular and square hollow sections), two grades of concrete infill (C30 and C60), two thicknesses of tube wall for each cross-section (6 and 10 mm), and five loading eccentricity ratios (0, 0.2, 0.3, 0.4 and 0.5). The CFSST stub column specimens were loaded in compression, with different loading eccentricities applied to achieve a wide range of axial load-to-bending moment ratios. This research provides a comprehensive report on the experimental methodology and subsequent observations, including the failure modes, load-deformation curves, axial load-bending moment curves, strain development at the key locations and values of ductility index. It can be observed that for circular CFSST columns, ultimate load decreased by roughly 70% with an increase in loading eccentricity ratios from 0 to 0.5, while for square columns, the reduction was about 50% under same conditions. The experimental results were used to evaluate if the existing design provisions for carbon steel-concrete composite structures is capable of designing the investigated CFSST stub columns. It was found that the mean ultimate load to predicted failure load ratios are 1.25, 1.32, and 1.36, with coefficients of variations (COV) equal to 0.08, 0.09 and 0.11, for the European, American, and Chinese codes, respectively. Consequently, the design approach specified in the Chinese code led to the most conservative and scattered strength predictions among the three codified design approaches. In contrast, the European code provides the most precise predictions of the test results, though there still remains scope for improvements in the ultimate resistance predictions of CFSST stub columns subjected to combined compression and bending.

Hip contact forces can be predicted with a neural network using only synthesised key points and electromyography in people with hip osteoarthritis

ObjectiveTo develop and validate a neural network to estimate hip contact forces (HCF), and lower body kinematics and kinetics during walking in individuals with hip osteoarthritis (OA) using synthesised anatomical key points and electromyography. To assess the capability of the neural network to detect directional changes in HCF resulting from prescribed gait modifications. DesignA calibrated electromyography-informed neuromusculoskeletal model was used to compute lower body joint angles, moments, and HCF for 17 participants with mild-to-moderate hip OA. Anatomical key points (e.g., joint centres) were synthesised from marker trajectories and augmented with bias and noise expected from computer vision-based pose estimation systems. Temporal convolutional and long short-term memory neural networks were trained using leave-one-subject-out validation to predict neuromusculoskeletal modelling outputs from the synthesised key points and measured electromyography data from 5 hip-spanning muscles. ResultsHCF was predicted with an average error of 13.4±7.1% of peak force. Joint angles and moments were predicted with an average root-mean-square-error of 5.3 degrees and 0.10 Nm/kg, respectively. The NN could detect changes in peak HCF that occur due to gait modifications with good agreement with neuromusculoskeletal modelling (r2 = 0.72) and a minimum detectable change of 9.5%. ConclusionThe developed neural network predicted HCF and lower body joint angles and moments in individuals with hip OA using noisy synthesised key point locations with acceptable errors. Changes in HCF magnitude due to gait modifications were predicted with high accuracy. These findings have important implications for implementation of load-modification based gait retraining interventions for people with hip OA in a natural environment (i.e., home, clinic).

Integrating category-related key regions with a dual-stream network for remote sensing scene classification

Remote sensing image scene classification has made great progress with deep learning. Due to complex backgrounds and the large number of objects with inhomogeneous sizes, remote sensing image scene classification still remains challenging. In fact, only a few parts of regions are expected to be representative of the scene. In this paper, we propose a dual-stream framework for remote sensing classification with the help of category-related regions. Swin Transformer-based global feature extractor is used to produce coarse classification results. A category-related key region localization module is developed to extract the representative region from the whole image. The ResNet50 is employed as a local feature extractor to mine critical features from prominent regions. Finally, the classification results is obtained with the shared weighted classify head on global-local features. Extensive experiments show that our method provides a promising approach for key region locations and performs best on three public remote sensing datasets.

TSwinPose: Enhanced monocular 3D human pose estimation with JointFlow

Monocular estimation of 3D human poses is challenging due to ambiguity in depths and partial occlusion. Most recent works define this as a 2D-to-3D lifting task, taking 2D key point sequences and using spatial and temporal relationships. However, prior works focus on capturing spatio-temporal correlations but ignore the motion of joints that is needed for continuous estimation. To extend the potential of 2D-to-3D pose estimation, we propose TSwinPose, which learns multi-scale spatio-temporal representations from 2D key point locations and patterns of motion. The input 2D key point sequences are enhanced by JointFlow, which encodes the motion of each human joint. Based on Swin-Transformer, we designed a temporal domain Swin-Unet structure to model multi-scale spatio-temporal relationships of human joints across different temporal windows. The final 3D pose generated by multi-stage representations is consistent temporally and has a higher accuracy. Experiments conducted on three benchmark datasets, Human3.6M, MPI-INF-3DHP, and HumanEva-I, demonstrate that TSwinPose achieves performance that is on par with state-of-the-art methods. Moreover, the introduction of JointFlow as a plug-in extension enhances performance significantly, particularly benefiting long-term 2D-to-3D lifting human pose estimation methods.

Voices in a pandemic: using deep mapping to explore children’s sense of place during the COVID-19 pandemic in UK

ABSTRACT Children’s sense of place is important for wellbeing, development and belonging in a community or place. The VIP-CLEAR (Voices in a Pandemic – Children’s Lockdown Experiences Applied to Recovery) project used creative methods and repeat engagement to capture children’s experiences of the COVID-19 pandemic in socially disadvantaged, urban settings, in Bristol, UK. This paper focuses on findings from the two-phased ‘deep mapping’ activity conducted in schools with 6–11-year-olds to consider children’s sense of place at this time. Children’s maps showed how their mobility was restricted to the home and/or adult-controlled, looped routes for functional tasks rather than child-directed exploration. Key locations - including school, family houses, and parks - were disconnected and highlighted as sites of ‘absence’, where children were excluded. These places were given meaning due to pre-COVID practice, sensory experience, and/or their relationship with valued people. As pandemic mitigation relaxed, children’s maps showed increasing connections and greater visibility of the community and non-essential activities. As places changed, the amplification of existing social inequalities became apparent. In both phases, sense of place evolved and digital and natural spaces (through animals) showed potential for children to increase practice and connections with place. A strong sense of place may support adaptation to change, and this paper contributes to limited research on how children’s sense of place is dynamic, altering with fluctuating social and environmental conditions, e.g. mitigation of a global pandemic. The implications of findings on future recovery planning involving children are also considered.

Quantitative pressure and saturation engineering values from 4D PP and PS seismic data

AbstractFor field development and drilling decisions, production assets and reservoir engineers require dynamic reservoir properties, such as saturation and pressure changes of a reservoir from the pre‐production virgin state. To date, geophysicists have produced time‐lapse (4D) seismic attributes (mostly on stacked seismic data) rather than dynamic parameters directly. In this paper, we present a new method to estimate saturation and pressure properties from time‐lapse seismic data to provide to reservoir engineers. This new three‐step method is demonstrated over the Edvard Grieg field in the North Sea. We can realize this method thanks to advanced seismic multi‐component acquisition via PP and PS seismic data and processing that allows accurate estimation of amplitude‐variation‐with‐offset parameters P‐ and S‐impedances. With time‐lapse P‐ and S‐impedances optimally resolved, we estimate a stable set of axes identifying water saturation increase (water replacing oil), gas saturation increase (gas injection or gas out of solution), pressure increase (at injectors) and pressure decrease (at producers). Once these axes are obtained, we convert every 4D P‐ and S‐impedance data points into 4D pseudo‐saturation and pseudo‐pressure using a transformation of coordinates. We next use the rock physics relationships of this field to show that a linear relationship can be used to map any 4D change in the field from impedances to saturations and pressures. Key locations in the field with largest saturation and pressure changes are used to find calibration values at these extreme points. Next, from the pseudo‐seismic 4D data, a linear mapping is used to calculate actual reservoir property changes (fractions for saturation and bars for pressure). This allows us to obtain fieldwide dynamic values for water and gas saturations and injection and production related pressure changes. The results are shown, and dynamic changes are interpreted on the Edvard Grieg field data.

Effect of twisting of intravitreal injections on ocular bio-mechanics: a novel insight to ocular surgery.

Although intravitreal (IVT) injections provide several advantages in treating posterior segment eye diseases, several associated challenges remain. The current study uses the finite element method (FEM) to highlight the effect of IVT needle rotation along the insertion axis on the reaction forces and deformation inside the eye. A comparison of the reaction forces at the eye's key locations has been made with and without rotation. In addition, a sensitivity analysis of various parameters, such as the needle's angular speed, insertion location, angle, gauge, shape, and intraocular pressure (IOP), has been carried out to delineate the individual parameter's effect on reaction forces during rotation. Results demonstrate that twisting the needle significantly reduces the reaction forces at the penetration location and throughout the needle travel length, resulting in quicker penetration. Moreover, ocular biomechanics are influenced by needle insertion location, angle, shape, size, and IOP. The reaction forces incurred by the patient may be reduced by using a bevel needle of the higher gauge when inserted close to the normal of the local scleral surface toward the orra serrata within the Pars Plana region. Results obtained from the current study can deepen the understanding of the twisting needle's interaction with the ocular tissue.

Modular Autonomous Vehicles’ Application in Public Transport Networks: Conceptual Analysis on Airport Connection

Increased efficiency and optimized operation of transport networks represent two of the main topics of interest when discussing modern road vehicle solutions. Taking steps towards more sustainable options, manufacturers of road vehicles are looking into advanced technologies that allow vehicles to run more efficiently and take advantage of all the available data on the road. When looking at public transportation applications, trends point in the direction of using varied types of vehicles that can carry people around. The intermodality of these types of vehicles represents the most optimized way of traveling, combining the fast and secure characteristics of airplanes and trains with the flexibility of last-mile options, such as taxis, buses, or trams. This paper discusses the aspects of implementing a modular autonomous vehicle (MAV) solution for the last-mile part of travel routes, connecting key points of a city, such as an airport or a train station, to other key locations in the city, such as the city center, important facilities, or marginal neighborhoods.

Experimental study on stiffness deterioration of cracked RC hollow-core slab beams

To accurately assess the performance degradation of RC hollow-slab beam after service, in-situ static load tests were carried out on a RC hollow-slab beam bridge with a span diameter of 11.25 m, which is part of the Chongqing–Chengdu Highway Viaduct. Indoor single-girder static load tests were also carried out to study the deflection concrete strain and reinforcement strain at key locations on the hollow-slab beam. Crack development was recorded to investigate the stiffness degradation law of hollow-core slabs. Inverse secant stiffness–residual deflection and inverse secant stiffness–maximum crack width relationship models were established. Results show that the calibration coefficients obtained in the in-situ static load tests were greater than one, indicating potential for stiffness deterioration and insufficient structural safety reserves during service. The initial crack width was increased and extended upwards before the test beam yielded, with many new vertical cracks in the pure bending zone which extended continuously. The slope of deflection curve was larger before yielding and smaller after yielding, the secant stiffness of RC hollow-slab beam was exponentially decreased with load before yielding and changed linearly with load after yielding. The inverse secant stiffness–residual deflection and inverse secant stiffness–maximum crack width curves of the test beam were approximately bilinear, with a larger slope at the beginning of the test and a smaller slope in the plastic phase.

Integrating physics-informed machine learning with resonance effect for structural dynamic performance modeling

Accurate prediction the dynamic response of structures under various loads is a complex and challenging task due to the uncertainties and intricacies of loading scenarios and analysis methods. Traditional approaches to structural analysis and modeling often rely on physics-based simulations, which can be computationally expensive and time-consuming. Over the years, Machine Learning (ML) methods have proven to be a formidable tool for data-driven modeling, based on in-situ monitoring data. However, these ML models are generally purely data-driven, lacking consideration for relevant physical information such as dynamic characteristics. Hence, this paper proposes a Physics-Informed Machine Learning (PIML) approach for modeling structural dynamic performance. This method embeds resonance effect, a crucial piece of physical information in real-world engineering, into the design of the multilayer perceptron (MLP) loss function. The model is validated through numerical simulations of forced vibrations in a single-degree-of-freedom system and a vehicle-bridge coupled system. The results indicate that the proposed PIML can model the system dynamic response effectively and simulate resonance effect at key frequency-domain locations accurately. Subsequently, features are extracted from the real-world monitoring data of a high-rise building dynamic response during Typhoon Hato, and PIML is applied for training. The results reveal that PIML significantly outperforms pure ML algorithms, even with a small dataset, and can effectively capture resonance effect in wind-induced vibrations. Using a well-trained PIML, a parameter analysis is conducted, comparing the dynamic performance under different wind speeds and frequency conditions. Lastly, considering the variation in wind parameters due to climate change, PIML is employed to analyze long-term structural fragility. The findings indicate significant changes in fragility from 1985 to 2045. In conclusion, the proposed PIML algorithm offers several advantages over conventional methods, such as reduced computational costs, improved accuracy, and the ability to capture complex nonlinear behaviors and resonance effect of interest, and efficiently serve in analyses of structural reliability and fragility.

Inventraset assemblages: The spatial logic of informal street vending, transport and settlement

Urban informality remains a central challenge for those engaged in understanding and transforming global South cities. There have been calls to develop new conceptual language geared to this challenge and much debate around the degree to which it might be subsumed within global urban theory. We argue that theories of informal urbanism need to be grounded in an understanding of how it works to sustain livelihoods, moving beyond studies of informal settlement, street vending and transport to understand the synergies, interrelations and interdependencies between them. Informal vending and transport provide employment and produce cheap goods and mobility; informal settlement produces affordable housing in key locations with access and mobility. ‘Inventraset’ is a portmanteau concept that links informal vending, transport and settlement into a dynamic urban assemblage that is inventive, transgressive and settled. This model is demonstrated through an empirical study of the spatial logic of the inventraset triangle within the megacities of Manila and Jakarta. Here the informal is normal, whether displayed in the intensities of transit nodes and street markets or camouflaged within zones of exclusion. This is not an ‘informal city’ but one where informal street vending, transport and settlement are geared to formal spatial and governance structures in different ways in different neighbourhoods − an assemblage of informal/formal and of vending/transport/settlement without which the urban economy would collapse. This is a call not simply to rename the informal but to understand it as a mode of production that is more than the inverse of the formal.

Analysis of Spatiotemporal Characteristics and Influencing Factors of Electric Vehicle Charging Based on Multisource Data

Amid the global shift towards sustainable development, this study addresses the burgeoning electric vehicle (EV) market and its infrastructure challenges, particularly the lag in public charging facility development. Focusing on Wuhan, it utilizes big data to analyze EV charging behavior’s spatiotemporal aspects and the urban environment’s influence on charging efficiency. Employing a random forest regression and multiscale geographically weighted regression (MGWR), the research elucidates the nonlinear interaction between urban infrastructure and charging station usage. Key findings include (1) a direct correlation between EV charging patterns and urban temporal factors, with notable price elasticity; (2) the predominant influence of commuting distance, supplemented by the availability of fast-charging options; and (3) a strategic proposal for increasing slow-charging facilities at key urban locations to balance operational costs and user demand. The study combines spatial analysis and charging behavior to recommend enhancements in public EV charging infrastructure layouts.

River-floodplain connectivity and residence times controlled by topographic bluffs along a backwater transition

The morphology of river levees and floodplains is an important control on river-floodplain connectivity within a river system under sub-bankfull conditions, and this morphology changes as a river approaches the coast due to backwater influence. Floodplain width can also vary along a river, and floodplain constrictions in the form of bluffs adjacent to the river can influence inundation extent. However, the relative controls of backwater-influenced floodplain topography and bluff topography on river-floodplain connectivity have not been studied. We measure discharge along the lower Trinity River (Texas, USA) during high flow to determine which floodplain features are associated with major river-floodplain flow exchanges. We develop a numerical model representing the transition to backwater-dominated river hydraulics, and quantify downstream changes in levee channelization, inundation, and fluxes along the river-floodplain boundary. We model passive particle transport through the floodplain, and compute residence times as a function of location where particles enter the floodplain. We find that bluff topography controls flow from the floodplain back to the river, whereas levee topography facilitates flow to the floodplain through floodplain channels. Return flow to the river is limited to locations just upstream of bluffs, even under receding flood conditions, whereas outflow locations are numerous and occur all along the river. Residence times for particles entering the floodplain far upstream of bluffs are as much as two orders of magnitude longer than those for particles entering short distances upstream of bluffs. This study can benefit floodplain ecosystem management and restoration plans by informing on the key locations of lateral exchange and variable residence time distributions in river-floodplain systems.