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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Understanding the tropical cloud feedback from an analysis of the circulation and stability regimes simulated from an upgraded multiscale modeling framework

As revealed from studies using conventional general circulation models (GCMs), the thermodynamic contribution to the tropical cloud feedback dominates the dynamic contribution, but these models have difficulty in simulating the subsidence regimes in the tropics. In this study, we analyze the tropical cloud feedback from a 2 K sea surface temperature (SST) perturbation experiment performed with a multiscale modeling framework (MMF). The MMF explicitly represents cloud processes using 2-D cloud-resolving models with an advanced higher-order turbulence closure in each atmospheric column of the host GCM. We sort the monthly mean cloud properties and cloud radiative effects according to circulation and stability regimes. Here, we find that the regime-sorted dynamic changes dominate the thermodynamic changes in terms of the absolute magnitude. The dynamic changes in the weak subsidence regimes exhibit strong negative cloud feedback due to increases in shallow cumulus and deep clouds while those in strongly convective and moderate-to-strong subsidence regimes have opposite signs, resulting in a small contribution to cloud feedback. On the other hand, the thermodynamic changes are large due to decreases in stratocumulus clouds in the moderate-to-strong subsidence regimes with small opposite changes in the weak subsidence and strongly convective regimes, resulting in a relatively large contribution to positive cloud feedback. The dynamic and thermodynamic changes contribute equally to positive cloud feedback and are relatively insensitive to stability in the moderate-to-strong subsidence regimes. But they are sensitive to stability changes from the SST increase in convective and weak subsidence regimes. Lastly, these results have implications for interpreting cloud feedback mechanisms.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Closed‐Loop Recycling of Mixed Plastics of Polyester and CO 2 ‐Based Polycarbonate to a Single Monomer

Abstract Physical blending is an effective strategy for tailoring polymeric materials to specific application requirements. However, physically blended mixed plastics waste adds additional barriers in mechanical or chemical recycling. This difficulty arises from the intricate requirement for meticulous sorting and separation of the various polymers in the inherent incompatibility of mixed polymers during recycling. To overcome this impediment, this work furthers the emerging single‐monomer – multiple‐materials approach through the design of a bifunctional monomer that can not only orthogonally polymerize into two different types of polymers – specifically lactone‐based polyester and CO 2 ‐based polycarbonate – but the resultant polymers and their mixture can also be depolymerized back to the single, original monomer when facilitated by catalysis. Specifically, the lactone/epoxide hybrid bifunctional monomer (BiL O ) undergoes ring‐opening polymerization through the lactone manifold to produce polyester, PE(BiL O ), and is also applied to ring‐opening copolymerization with CO 2 , via the epoxide manifold, to yield polycarbonate, PC(BiL O ). Remarkably, a one‐pot recycling process of a BiL O ‐derived PE/PC blend back to the constituent monomer BiL O in >99 % selectivity was achieved with a superbase catalyst at 150 °C, thereby effectively obviating the requirement for sorting and separation typically required for recycling of mixed polymers.

Shi, Changxia↗
DOE OSTI2024

Closed‐Loop Recycling of Mixed Plastics of Polyester and CO 2 ‐Based Polycarbonate to a Single Monomer

Abstract Physical blending is an effective strategy for tailoring polymeric materials to specific application requirements. However, physically blended mixed plastics waste adds additional barriers in mechanical or chemical recycling. This difficulty arises from the intricate requirement for meticulous sorting and separation of the various polymers in the inherent incompatibility of mixed polymers during recycling. To overcome this impediment, this work furthers the emerging single‐monomer – multiple‐materials approach through the design of a bifunctional monomer that can not only orthogonally polymerize into two different types of polymers – specifically lactone‐based polyester and CO 2 ‐based polycarbonate – but the resultant polymers and their mixture can also be depolymerized back to the single, original monomer when facilitated by catalysis. Specifically, the lactone/epoxide hybrid bifunctional monomer (BiL O ) undergoes ring‐opening polymerization through the lactone manifold to produce polyester, PE(BiL O ), and is also applied to ring‐opening copolymerization with CO 2 , via the epoxide manifold, to yield polycarbonate, PC(BiL O ). Remarkably, a one‐pot recycling process of a BiL O ‐derived PE/PC blend back to the constituent monomer BiL O in >99 % selectivity was achieved with a superbase catalyst at 150 °C, thereby effectively obviating the requirement for sorting and separation typically required for recycling of mixed polymers.

Chemistry↗
DOE OSTI2020

Sampling and resolution characteristics in reduced order models of shallow water equations: Intrusive vs nonintrusive

We investigate the sensitivity of reduced order models (ROMs) to training data spatial resolution as well as sampling rate. In particular, we consider proper orthogonal decomposition (POD), coupled with Galerkin projection (POD-GP), as an intrusive reduced order modeling technique. For non-intrusive ROMs, we consider two frameworks. The first is using dynamic mode decomposition (DMD), and the second is based on artificial neural networks (ANNs). For ANN, we utilized a residual deep neural network, and for DMD we have studied two versions of DMD approaches; one with hard thresholding and the other with sorted bases selection. Also, we highlight the differences between mean-subtracting the data (centering) and using the data without mean-subtraction. We tested these ROMs using a system of 2D shallow water equations for four different numerical experiments, adopting combinations of sampling rates and spatial resolutions. For these cases, we found that the DMD basis obtained with hard threshodling is sensitive to sampling rate. The sorted DMD algorithm helps to mitigate this problem and yields more stabilized and converging solution. Furthermore, we demonstrate that both DMD approaches without mean subtraction provide significantly more accurate results than DMD with mean-subtracting the data. On the other hand, POD is relatively insensitive to sampling rate and yields better representation of the flow field. Meanwhile, spatial resolution has little effect on both POD and DMD performances. Here, the numerical results reveal that an ANN on POD subspace (POD-ANN) performs remarkably better than POD-GP and DMD in capturing system dynamics, even with a small number of modes.

42 ENGINEERING↗
DOE OSTI2016

A Pareto Algorithm for Efficient De Novo Design of Multi-functional Molecules

Here, we have introduced a Pareto sorting algorithm into Synopsis, a de novo design program that generates synthesizable molecules with desirable properties. We give a detailed description of the algorithm and illustrate its working in 2 different de novo design settings: the design of putative dual and selective FGFR and VEGFR inhibitors, and the successful design of organic structure determining agents (OSDAs) for the synthesis of zeolites. We show that the introduction of Pareto sorting not only enables the simultaneous optimization of multiple properties but also greatly improves the performance of the algorithm to generate molecules with hard-to-meet constraints. This in turn allows us to suggest approaches to address the problem of false positive hits in de novo structure based drug design by introducing structural and physicochemical constraints in the designed molecules, and by forcing essential interactions between these molecules and their target receptor.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Hierarchical computation in the SPMD programming model

Large-scale parallel machines are programmed mainly with the single program, multiple data (SPMD) model of parallelism. While this model has advantages of scalability and simplicity, it does not fit well with divide-and-conquer parallelism or hierarchical machines that mix shared and distributed memory. In this paper, we define the recursive single program, multiple data model (RSPMD) that extends SPMD with a hierarchical team mechanism to support hierarchical algorithms and machines. We implement this model in the Titanium language and describe how to eliminate a class of deadlocks by ensuring alignment of collective operations. We present application case studies evaluating the RSPMD model, showing that it enables divide-and-conquer algorithms such as sorting to be elegantly expressed and that team collective operations increase performance of conjugate gradient by up to a factor of two. The model also facilitates optimizations for hierarchical machines, improving scalability of particle in cell by 8x and performance of sorting and a stencil code by up to 40% and 14%, respectively.

Kamil, A↗
DOE OSTI2021

Parameter inference from event ensembles and the top-quark mass

One of the key tasks of any particle collider is measurement. In practice, this is often done by fitting data to a simulation, which depends on many parameters. Sometimes, when the effects of varying different parameters are highly correlated, a large ensemble of data may be needed to resolve parameter-space degeneracies. An important example is measuring the top-quark mass, where other physical and unphysical parameters in the simulation must be profiled when fitting the top-quark mass parameter. We compare four different methodologies for top-quark mass measurement: a classical histogram fit similar to one commonly used in experiment augmented by soft-drop jet grooming; a 2D profile likelihood fit with a nuisance parameter; a machine-learning method called DCTR; and a linear regression approach, either using a least-squares fit or with a dense linearly-activated neural network. Despite the fact that individual events are totally uncorrelated, we find that the linear regression methods work most effectively when we input an ensemble of events sorted by mass, rather than training them on individual events. Although all methods provide robust extraction of the top-quark mass parameter, the linear network does marginally best and is remarkably simple. For the top study, we conclude that the Monte-Carlo-based uncertainty on current extractions of the top-quark mass from LHC data can be reduced significantly (by perhaps a factor of 2) using networks trained on sorted event ensembles. More generally, machine learning from ensembles for parameter estimation has broad potential for collider physics measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

TLR4 plays a crucial role in MSC-induced inhibition of NK cell function

Mesenchymal stem cells (MSC) are a kind of stromal cell within the tumor microenvironment. In our research, MSC derived from acute myeloid leukemia patients' bone marrow (AML-MSC) and lung cancer tissues (LC-MSC) as well as normal bone marrow-derived MSC (BM-MSC) cultured in conditioned medium of HeLa cells were found to have higher expressions of Toll-like receptor (TLR4) mRNA compared with BM-MSC. The sorted TLR4-positive MSC (TLR4+ MSC) differed in cytokine (interleukin-6, interleukin-8, and monocyte chemoattractant protein-1) secretion from those of unsorted MSC. MSC was reported to inhibit natural killer (NK) cell proliferation and function. In this research, we confirmed that TLR4+ MSC aggravate this suppression. Furthermore, when TLR4 in the sorted cells were stimulated by LPS or following blocked by antibody, the suppression on NK cell proliferation and cytotoxicity were more intensive or recovered respectively. Compared to unsorted MSC, NKG2D receptor expression on NK cells were also inhibited by TLR4+ MSC. These findings suggest that activation of TLR4 pathway is important for TLR4+ MSC and MSC to obstruct anti-tumor immunity by inhibiting NK cell function, which may provide a potential stroma-targeted tumor therapy. - Highlights: • TLR4+ MSC inhibit NK cell proliferation in vivo and in vitro. • TLR4+ MSC inhibit NKG2D expression on NK cells and NK cell cytotoxicity. • The distinguished cytokine expression of TLR4+ MSC may contribute to the inhibition on NK cell function.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

APBB1 reinforces cancer stem cell and epithelial-to-mesenchymal transition by regulating the IGF1R signaling pathway in non-small-cell lung cancer cells

Amyloid β precursor protein binding family B member 1(APBB1) was first identified as a binding partner of amyloid precursor protein during brain development, but its function in the context of cancer remain unclear. Here we show for the first time that APBB1 is partly associated with intensifying cancer stem cell(CSC) and epithelial-to-mesenchymal transition (EMT) and enhancing radiation-resistant properties of lung cancer cells. We found that APBB1 was highly expressed in ALDH1{sup high} CSC-like cells sorted from A549 lung cancer cells. In APBB1-deficient H460 cells with forced overexpression of APBB1, the protein directly interacted with IGF1Rβ, enhanced phosphorylation of IGF1Rβ/PI3K/AKT pathway(activation) and subsequently induced the phosphorylation of GSK3β(inactivation). This phosphorylation stabilized Snail1, a negative regulator of E-cadherin expression, and regulated β-catenin–mediated ALDH1 expression, which are representative markers for EMT and CSCs, respectively. In contrast, suppression of APBB1 expression with siRNA yielded the opposite effects in APBB1-rich A549 cells. We concluded that APBB1 partly regulates the expression of ALDH1. We also found that APBB1 regulates activation of nuclear factor-κB, which is involved in reducing various stresses including oxidative stress, which suggests that APBB1 is associated with γ-radiation sensitivity. Our findings imply that APBB1 plays an important role in the maintenance of EMT-associated CSC-like properties and γ-radiation resistance via activation of IGF1Rβ/AKT/GSK3β pathway in lung cancer cells, highlighting APBB1 as a potential target for therapeutic cancer treatment. - Highlights: • APBB1 was highly expressed in ALDH1{sup high} cells sorted from A549 cells. • APBB1 is associated with intensifying CSC and EMT and enhancing radiation-resistant properties of lung cancer cells. • APBB1 regulates EMT-associated CSC-like properties and γ-radiation resistance via activation of IGF1Rβ/AKT/GSK3β pathway. • APBB1 partly regulates the expression of ALDH1 via AKT/GSK3β-associated β-catenin pathway.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Integrative analysis of rewired central metabolism in temozolomide resistant cells

Highlights: • Temozolomide (TMZ) resistant Neurospheroids (NSP) identified in U87MG cell line. • NSP shows varied dose response, two fold higher IC{sub 50} and 30% lower growth rate. • Altered Glucose and Glutamine uptake in U87MG and NSP shapes metabolic dynamics. • Differential mRNA levels of CAN genes & ABC transporters drive respiration/growth. • Integrative paradigm identifies potential metabolic drivers for TMZ resistance. An authenticated U87MG clonal glioblastoma cell line was investigated to identify a sub-population of neurospheroidal (NSP) cells within the main epithelial population (U87MG). The NSP cells sorted using Fluorescence Assisted Cell Sorting (FACS) showed varied morphology, 30% lower growth rates, 40% higher IC{sub 50} values for temozolomide drug and could differentiate into the glial cell type (NDx). Metabolite profiling using HR-LCMS identified glucose, glutamine and serine in both populations and tryptophan only in U87MG as growth limiting substrates. Glycine, alanine, glutamate and proline were secreted by U87MG, however proline and glycine were re-utilized in NSP. Exo-metabolite profiling and phenotypic microarrays identified differential metabolism of primary carbon sources glucose and derived pyruvate for U87MG; glutamine and derived glutamate metabolism in NSP. Differential mRNA abundance of AKT1, PTEN, PIK3CA controlling metabolism, drug efflux, nutrient transport and epigenetic control MDM2 are potentially critical in shaping DNA methylation effects of temozolomide. Our study provides a new insight into the combined effect of these factors leading to temozolomide resistance in NSP.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Effects of PQ's cytotoxicity on secretory vesicles in astroglia: Expression alternation of secretogranin II and its potential interaction with intracellular factors

Highlights: • PQ upregulated SCG2 expression and altered its subcellular location in astroglia. • SCG2 knockdown dysregulated GS and IL-6 expressions on RNA and protein levels. • SCG2-positive LDCVs were partially involved in trafficking of IL-6 but not GS. • SCG2 may contribute to PQ toxicology by regulating neurotransmitters and cytokines. It has been extensively characterized that paraquat (PQ) selectively targets to the substantia nigra and exerts neurotoxic actions on dopaminergic neurons. However, a little knowledge is available about astroglia in PQ exposure, especially its complex secretory machinery. To explore this point, we built up a PQ-induced model in cultural U118 astrocyte. Since the granin family is considered as a master regulator of cargo sorting and large dense core vesicles (LDCVs) biogenesis in the regulated secretory pathway of nervous and neuroendocrine cells, the current study focused on one member, secretogranin II (SCG2) and investigated its alternation and potential relationship with other astrocyte-derived factors under PQ insult. We found that PQ upregulated SCG2 expression on both RNA and protein levels and stimulated the mRNA expression of neurotrophic factors, cytokines and glutamine synthetase (GS) simultaneously. RNAi knockdown of SCG2 did not rescue the cell cycle arrest induced by PQ but affected expressions of IL-6 and GS on mRNA and protein levels. Further studies on subcellular location showed that SCG2-positive secretory granules were partially colocalized with IL-6 but not GS in PQ exposure astrocyte. Taken together, our findings indicate that the expression alternation of SCG2 under astroglial activation by PQ may be necessary compensation for cargo sorting and LDCV biogenesis. The involvement of the IL-6 and GS suggests that the SCG2 may potentially regulate inflammatory factors and excitatory neurotransmitter to the cytotoxicity of PQ on astroglia.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Incorporation, intracellular trafficking and processing of extracellular heparanase by mast cells: Involvement of syndecan-4-dependent pathway

Highlights: • Exogenous proheparanase is internalized and sorted into mast cell secretory granules. • Incorporated heparanase is processed into a mature and an active form. • Syndecan-4 is involved in the heparanase uptake pathway. We investigated the fate of proheparanase added to the culture media of mast cells. A recombinant protein mimicking proheparanase was continuously internalized into mastocytoma cells as well as bone marrow- and peritoneal cell-derived mast cells. Internalized heparanase molecules were accumulated in granules and a significant portion was released by stimulation with ionomycin, indicating that the internalized heparanase was sorted into secretory granules. The pro-form heparanase was processed into a mature and an active form inside the cells, in which intracellular heparin was fragmented by the mature enzyme. The internalization was substantially inhibited by addition of heparin and heparan sulfate to the culture medium, suggesting that glycosaminoglycan is involved in the uptake pathway. Out of four syndecans, expression of syndecan-3 and syndecan-4, especially cell surface syndecan-4, was detected in the mastocytoma cells. Two knockdown clones transfected with a shRNA expression vector targeting the syndecan-4 gene took up significantly lower amounts of heparanase than mock cells. We propose that some exogenous substances like proheparanase can be incorporated into mast cell granules via a glycosaminoglycan-mediated, especially syndecan-4-dependent, uptake pathway.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

PACS-1 and adaptor protein-1 mediate ACTH trafficking to the regulated secretory pathway

Highlights: • PACS-1 and AP-1 play critical roles in targeting ACTH to the regulated secretory pathway. • PACS-1 and AP-1 promote the intracellular storage of ACTH. • In the absence of PACS-1 and AP-1, ACTH is constitutively secreted. • PACS-1 localizes to ACTH-positive vesicles in an AP-1-dependent manner. The regulated secretory pathway is a specialized form of protein secretion found in endocrine and neuroendocrine cell types. Pro-opiomelanocortin (POMC) is a pro-hormone that utilizes this pathway to be trafficked to dense core secretory granules (DCSGs). Within this organelle, POMC is processed to multiple bioactive hormones that play key roles in cellular physiology. However, the complete set of cellular membrane trafficking proteins that mediate the correct sorting of POMC to DCSGs remain unknown. Here, we report the roles of the phosphofurin acidic cluster sorting protein – 1 (PACS-1) and the clathrin adaptor protein 1 (AP-1) in the targeting of POMC to DCSGs. Upon knockdown of PACS-1 and AP-1, POMC is readily secreted into the extracellular milieu and fails to be targeted to DCSGs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2011

Interfraction Liver Shape Variability and Impact on GTV Position During Liver Stereotactic Radiotherapy Using Abdominal Compression

Purpose: For patients receiving liver stereotactic body radiotherapy (SBRT), abdominal compression can reduce organ motion, and daily image guidance can reduce setup error. The reproducibility of liver shape under compression may impact treatment delivery accuracy. The purpose of this study was to measure the interfractional variability in liver shape under compression, after best-fit rigid liver-to-liver registration from kilovoltage (kV) cone beam computed tomography (CBCT) scans to planning computed tomography (CT) scans and its impact on gross tumor volume (GTV) position. Methods and Materials: Evaluable patients were treated in a Research Ethics Board-approved SBRT six-fraction study with abdominal compression. Kilovoltage CBCT scans were acquired before treatment and reconstructed as respiratory sorted CBCT scans offline. Manual rigid liver-to-liver registrations were performed from exhale-phase CBCT scans to exhale planning CT scans. Each CBCT liver was contoured, exported, and compared with the planning CT scan for spatial differences, by use of in house-developed finite-element model-based deformable registration (MORFEUS). Results: We evaluated 83 CBCT scans from 16 patients with 30 GTVs. The mean volume of liver that deformed by greater than 3 mm was 21.7%. Excluding 1 outlier, the maximum volume that deformed by greater than 3 mm was 36.3% in a single patient. Over all patients, the absolute maximum deformations in the left-right (LR), anterior-posterior (AP), and superior-inferior directions were 10.5 mm (SD, 2.2), 12.9 mm (SD, 3.6), and 5.6 mm (SD, 2.7), respectively. The absolute mean predicted impact of liver volume displacements on GTV by use of center of mass displacements was 0.09 mm (SD, 0.13), 0.13 mm (SD, 0.18), and 0.08 mm (SD, 0.07) in the left-right, anterior-posterior, and superior-inferior directions, respectively. Conclusions: Interfraction liver deformations in patients undergoing SBRT under abdominal compression after rigid liver-to-liver registrations on respiratory sorted CBCT scans were small in most patients (<5 mm).

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

Techno-economics of hydrocarbon fuel production and recyclables recovery from landfill-destined municipal solid waste: AI-enhanced materials recovery facility design

Sustainable aviation fuels (SAF) production from cellulosic paper fractions of municipal solid waste (MSW) destined for landfills has strong potential to advance environmental, social, and economic sustainability across the aviation and waste sectors. This study proposes an artificial intelligence-enabled material recovery facility (AI-MRF) design to efficiently characterize, separate, process, and convert recovered paper waste from MSW into intermediate chemicals and SAF. The AI-MRF, designed to process 233,091 metric tons of MSW annually, integrates smart manufacturing technologies including AI, visual and hyperspectral imaging, multi-sensor data, and traditional sorting systems. Well-characterized and sorted cellulosic paper waste was utilized for chemical and fuel production scenarios, while clean plastics, metals, and glass were considered for recycling. Conversion of paper waste into intermediate sugars achieved a net present value (NPV) of up to $\$67$ million. For sugar-to-SAF production scenarios, the minimum fuel selling price (MFSP) was calculated at $\$6.11$ per gasoline gallon equivalent (GGE) when excluding recyclable revenue, and $\$4.03$ per GGE when halving recyclable revenue. The MFSP was further reduced to $\$1.96$ per GGE when accounting for SAF sales and recyclables. Nationally, this approach could yield about 2 billion GGE of hydrocarbon fuel annually from available MSW in the United States.

09 BIOMASS FUELS↗
DOE OSTI2011

Parallel-vector algorithms for particle simulations on shared-memory multiprocessors

Over the last few decades, the computational demands of massive particle-based simulations for both scientific and industrial purposes have been continuously increasing. Hence, considerable efforts are being made to develop parallel computing techniques on various platforms. In such simulations, particles freely move within a given space, and so on a distributed-memory system, load balancing, i.e., assigning an equal number of particles to each processor, is not guaranteed. However, shared-memory systems achieve better load balancing for particle models, but suffer from the intrinsic drawback of memory access competition, particularly during (1) paring of contact candidates from among neighboring particles and (2) force summation for each particle. Here, novel algorithms are proposed to overcome these two problems. For the first problem, the key is a pre-conditioning process during which particle labels are sorted by a cell label in the domain to which the particles belong. Then, a list of contact candidates is constructed by pairing the sorted particle labels. For the latter problem, a table comprising the list indexes of the contact candidate pairs is created and used to sum the contact forces acting on each particle for all contacts according to Newton's third law. With just these methods, memory access competition is avoided without additional redundant procedures. The parallel efficiency and compatibility of these two algorithms were evaluated in discrete element method (DEM) simulations on four types of shared-memory parallel computers: a multicore multiprocessor computer, scalar supercomputer, vector supercomputer, and graphics processing unit. The computational efficiency of a DEM code was found to be drastically improved with our algorithms on all but the scalar supercomputer. Thus, the developed parallel algorithms are useful on shared-memory parallel computers with sufficient memory bandwidth.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Impact of mixed grain size sediment input on braided river Morphodynamics: Insights from experimental and numerical modeling

The rate of sediment supply has significant impacts on river morphology, making it crucial to understand the geomorphic changes and grain size distribution dynamics in rivers. However, the effects of varying grain size sediment input on morphological changes in braided channels remain poorly understood. This study is the first to investigate the bar development and sediment sorting processes in braided channels with non-uniform sediment inputs using both numerical and experimental approaches. We applied a two-dimensional numerical model, Nays2DH to confirm and generalize experimental results. The model reproduced key experiment results, including 1) stream elevation changes, and 2) grain size distribution. Using this validated model, we explored the morphological changes and sorting process in a braided river with sediment inputs. The numerical experiments demonstrate that sediment input controls the elevation of the stream bed and the grain size distribution. Notably, both the elevation and grain-size distribution become relatively stable in downstream of the channel. Additionally, the simulation results suggest that an increased sediment supply leads to greater channel complexity, with bed surface armoring decreasing.

Nays2DH↗