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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

A rule for selecting analytical boundary conditions for the conservative quasi-one-dimensional nozzle flow equations

For the one-dimensional nozzle flow equations, the number of analytical boundary conditions that may be applied corresponds to the number of exterior characteristics reaching the boundary points. Since the slopes of the characteristics are the characteristic speeds u, u+c, and u-c, one concludes that two analytical boundary conditions are required at a subsonic inflow boundary and one at a subsonic outflow boundary. However, using this guideline alone can lead to nonunique solutions in subsonic cases. This paper presents a rule for selecting analytical boundary conditions for the dependent variables which will yield unique solutions if they exist.

Wornom, S. F.↗
NASA NTRS1996

A Three-Dimensional Linearized Unsteady Euler Analysis for Turbomachinery Blade Rows

A three-dimensional, linearized, Euler analysis is being developed to provide an efficient unsteady aerodynamic analysis that can be used to predict the aeroelastic and aeroacoustic response characteristics of axial-flow turbomachinery blading. The field equations and boundary conditions needed to describe nonlinear and linearized inviscid unsteady flows through a blade row operating within a cylindrical annular duct are presented. In addition, a numerical model for linearized inviscid unsteady flow, which is based upon an existing nonlinear, implicit, wave-split, finite volume analysis, is described. These aerodynamic and numerical models have been implemented into an unsteady flow code, called LINFLUX. A preliminary version of the LINFLUX code is applied herein to selected, benchmark three-dimensional, subsonic, unsteady flows, to illustrate its current capabilities and to uncover existing problems and deficiencies. The numerical results indicate that good progress has been made toward developing a reliable and useful three-dimensional prediction capability. However, some problems, associated with the implementation of an unsteady displacement field and numerical errors near solid boundaries, still exist. Also, accurate far-field conditions must be incorporated into the FINFLUX analysis, so that this analysis can be applied to unsteady flows driven be external aerodynamic excitations.

Montgomery, Matthew D.↗
NASA NTRS1989

Analytic theory for the selection of 2-D needle crystal at arbitrary Peclet number

An accurate analytic theory is presented for the velocity selection of a two-dimensional needle crystal for arbitrary Peclet number for small values of the surface tension parameter. The velocity selection is caused by the effect of transcendentally small terms which are determined by analytic continuation to the complex plane and analysis of nonlinear equations. The work supports the general conclusion of previous small Peclet number analytical results of other investigators, though there are some discrepancies in details. It also addresses questions raised on the validity of selection theory owing to assumptions made on shape corrections at large distances from the tip.

Tanveer, Saleh↗
DOE OSTI2021

Hybrid of multi‐dimensional fillers for thermally enhanced polyamide 12 composites fabricated by selective laser sintering

Abstract Selective laser sintering (SLS) is an additive manufacturing technology that can provide a novel strategy to manufacture complex polymer‐based composites with tailored properties. In this study, polyamide 12 (PA12) composite powders based on Al 2 O 3 , boron nitride (BN), and carbon nanotubes (CNTs) were prepared via a two‐step mixing approach. Morphology characterization techniques indicated that the fillers were uniformly dispersed in the PA12 matrix as expected. Under the optimum 3D‐printing parameters, the fabrication of SLS parts with high filler loading could be obtained. With 40 wt% Al 2 O 3 , 8 wt% BN, and 2 wt% CNT hybrid fillers, the thermal conductivity of PA12 composites could reach 1.09 W/mK. It could be attributed to the synergistic effect of multi‐dimensional fillers to form dense and continuous thermal conduction paths. The factors influencing the performance of PA12 composites such as melting and crystallization behaviors, dielectric properties, and mechanical properties were also discussed. The results show that these composites have favorable dielectric and mechanical properties. Overall, the PA12 composites fabricated by SLS technology in this study exhibit excellent thermal management ability.

Yuan, Yue↗
NASA NTRS2014

Automatic Aircraft Collision Avoidance System and Method

The invention is a system and method of compressing a DTM to be used in an Auto-GCAS system using a semi-regular geometric compression algorithm. In general, the invention operates by first selecting the boundaries of the three dimensional map to be compressed and dividing the three dimensional map data into regular areas. Next, a type of free-edged, flat geometric surface is selected which will be used to approximate terrain data of the three dimensional map data. The flat geometric surface is used to approximate terrain data for each regular area. The approximations are checked to determine if they fall within selected tolerances. If the approximation for a specific regular area is within specified tolerance, the data is saved for that specific regular area. If the approximation for a specific area falls outside the specified tolerances, the regular area is divided and a flat geometric surface approximation is made for each of the divided areas. This process is recursively repeated until all of the regular areas are approximated by flat geometric surfaces. Finally, the compressed three dimensional map data is provided to the automatic ground collision system for an aircraft.

Skoog, Mark↗
NASA NTRS1994

Direct numerical simulations and modeling of a spatially-evolving turbulent wake

Understanding of turbulent free shear flows (wakes, jets, and mixing layers) is important, not only for scientific interest, but also because of their appearance in numerous practical applications. Turbulent wakes, in particular, have recently received increased attention by researchers at NASA Langley. The turbulent wake generated by a two-dimensional airfoil has been selected as the test-case for detailed high-resolution particle image velocimetry (PIV) experiments. This same wake has also been chosen to enhance NASA's turbulence modeling efforts. Over the past year, the author has completed several wake computations, while visiting NASA through the 1993 and 1994 ASEE summer programs, and also while on sabbatical leave during the 1993-94 academic year. These calculations have included two-equation (K-omega and K-epsilon) models, algebraic stress models (ASM), full Reynolds stress closure models, and direct numerical simulations (DNS). Recently, there has been mutually beneficial collaboration of the experimental and computational efforts. In fact, these projects have been chosen for joint presentation at the NASA Turbulence Peer Review, scheduled for September 1994. DNS calculations are presently underway for a turbulent wake at Re(sub theta) = 1000 and at a Mach number of 0.20. (Theta is the momentum thickness, which remains constant in the wake of a two dimensional body.) These calculations utilize a compressible DNS code written by M. M. Rai of NASA Ames, and modified for the wake by J. Cimbala. The code employs fifth-order accurate upwind-biased finite differencing for the convective terms, fourth-order accurate central differencing for the viscous terms, and an iterative-implicit time-integration scheme. The computational domain for these calculations starts at x/theta = 10, and extends to x/theta = 610. Fully developed turbulent wake profiles, obtained from experimental data from several wake generators, are supplied at the computational inlet, along with appropriate noise. After some adjustment period, the flow downstream of the inlet develops into a fully three-dimensional turbulent wake. Of particular interest in the present study is the far wake spreading rate and the self-similar mean and turbulence profiles. At the time of this writing, grid resolution studies are underway, and a code is being written to calculate turbulence statistics from these wake calculations; the statistics will be compared to those from the ongoing PIV wake measurements, those of previous experiments, and those predicted by the various turbulence models. These calculations will lead to significant long-term benefits for the turbulence modeling effort. In particular, quantities such as the pressure-strain correlation and the dissipation rate tensor can be easily calculated from the DNS results, whereas these quantities are nearly impossible to measure experimentally. Improvements to existing turbulence models (and development of new models) require knowledge about flow quantities such as these. Present turbulence models do a very good job at prediction of the shape of the mean velocity and Reynolds stress profiles in a turbulent wake, but significantly underpredict the magnitude of the stresses and the spreading rate of the wake. Thus, the turbulent wake is an ideal flow for turbulence modeling research. By careful comparison and analysis of each term in the modeled Reynolds stress equations, the DNS data can show where deficiencies in the models exist; improvements to the models can then be attempted.

Cimbala, John M.↗
DOE OSTI2022

Solid-State Pathway Control via Reaction-Directing Heteroatoms: Ordered Pyridazine Nanothreads through Selective Cycloaddition

Nanothreads are one-dimensional nanomaterials comprised of a primarily sp 3 hydrocarbon backbone. They are typically formed through cycloaddition reactions induced by compression of small molecules to high pressures. Although nanothreads have been synthesized from a range of small molecule precursors (e.g., benzene, pyridine, aniline), the ability to control reaction pathways to produce atomically precise nanothreads with distinct chemical structures remains a difficult challenge. In this study, we show how heteroatoms incorporated within starting precursors can serve as “thread directing” groups by selecting for specific cycloaddition reaction pathways. By using a less-reactive diazine group within a six-membered aromatic ring, we successfully predict and synthesize the first carbon nanothread material derived from pyridazine (1,2-diazine, C 4 H 4 N 2 ). Compared with previous nanothreads, the synthesized polypyridazine, shows a predominantly uniform chemical structure with exceptional long-range order, allowing for structural characterization using vibrational spectroscopy and X-ray diffraction. The results demonstrate how thread-directing groups can be used for precise reaction pathway control and the formation of chemically precise nanothreads with a high degree of structural order.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

SPH with dynamical smoothing length adjustment based on the local flow kinematics

Due to the Lagrangian nature of Smoothed Particle Hydrodynamics (SPH), the adaptive resolution remains a challenging task. In this work, we first analyse the influence of the simulation parameters and the smoothing length on solution accuracy, in particular in high strain regions. Based on this analysis we develop a novel approach to dynamically adjust the kernel range for each SPH particle separately, accounting for the local flow kinematics. We use the Okubo–Weiss parameter that distinguishes the strain and vorticity dominated regions in the flow domain. The proposed development is relatively simple and implies only a moderate computational overhead. We validate the modified SPH algorithm for a selection of two-dimensional test cases: the Taylor–Green flow, the vortex spin-down, the lid-driven cavity and the dam-break flow against a sharp-edged obstacle. The simulation results show good agreement with the reference data and improvement of the long-term accuracy for unsteady flows. For the lid-driven cavity case, the proposed dynamical adjustment remedies the problem of tensile instability (particle clustering).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Origin of Phase Separation in Ni-Rich Layered Oxide Cathode Materials During Electrochemical Cycling

In intercalation materials, the kinetics and uniformity of mass transport across the nanocrystalline domains dictate the structural reversibility and transport capability at the macroscopic level. (De)intercalation-induced interlayer disintegrations exhibit anisotropic crystallite size change. Due to the anisotropic mass transport mechanism, separated phases are inherently crystallographically oriented. One such material is LiNi $1–x–y$ Mn $x$ Co $y$ O 2 , which plays a pivotal role in advanced Li-ion batteries but suffers from severe phase inhomogeneities under fast charge or electrochemical aging. Here, using operando synchrotron techniques, we probe the mechanistic origins of the compositional and orientational-dependent phase separations during the electrochemical cycling of LiNi 0.8 Mn 0.1 Co 0.1 O 2 by comprehensive analysis of both in-plane and out-of-plane reflections. In the H2/H3 phase regime, in-plane domain propagation occurs due to increased covalency despite the severe decay of interlayer crystallographic order, resulting in the change of crystalline domain shape from 3D spheres to two-dimensional nanosheets. The crystallographically selective XRD line splitting is linked to the geometry of the facets as mass transfers along the ab plane. In conclusion, this work provides mechanistic insights into crystallographic orientation-dependent phase inhomogeneity under fast charge and extended cycling.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Kinetic Control of Angstrom-Scale Porosity in 2D Lattices for Direct Scalable Synthesis of Atomically Thin Proton Exchange Membranes

Angstrom-scale pores introduced into atomically thin 2D materials offer transformative advances for proton exchange membranes in several energy applications. Here, we show that facile kinetic control of scalable chemical vapor deposition (CVD) can allow for direct formation of angstrom-scale proton-selective pores in monolayer graphene with significant hindrance to even small, hydrated ions (K + diameter ~6.6 Å) and gas molecules (H 2 kinetic diameter ~2.9 Å). We demonstrate centimeter-scale Nafion|Graphene|Nafion membranes with proton conductance ~3.3–3.8 S cm –2 (graphene ~12.7–24.6 S cm –2 ) and H + /K + selectivity ~6.2–44.2 with liquid electrolytes. The same membranes show proton conductance ~4.6–4.8 S cm –2 (graphene ~39.9–57.5 S cm –2 ) and extremely low H 2 crossover ~1.7 × 10 –1 – 2.2 × 10 –1 mA cm –2 (~0.4 V, ~25 °C) with H 2 gas feed. We rationalize our findings via a resistance-based transport model and introduce a stacking approach that leverages combinatorial effects of interdefect distance and interlayer transport to allow for Nafion|Graphene|Graphene|Nafion membranes with H + /K + selectivity ~86.1 (at 1 M) and record low H 2 crossover current density ~2.5 × 10 –2 mA cm –2 , up to ~90% lower than state-of-the-art ionomer Nafion membranes ~2.7 × 10 –1 mA cm –2 under identical conditions, while still maintaining proton conductance ~4.2 S cm –2 (graphene stack ~20.8 S cm –2 ) comparable to that for Nafion of ~5.2 S cm –2 . Furthermore, our experimental insights enable functional atomically thin high flux proton exchange membranes with minimal crossover.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Ultrafast band engineering and transient spin currents in antiferromagnetic oxides

Here, we report a dynamic structure and band engineering strategy with experimental protocols to induce indirect-to-direct band gap transitions and coherently oscillating pure spin-currents in three-dimensional antiferromagnets (AFM) using selective phononic excitations. In the Mott insulator LaTiO 3 , we show that a photo-induced nonequilibrium phonon mode amplitude destroys the spin and orbitally degenerate ground state, reduces the band gap by 160 meV and renormalizes the carrier masses. The time scale of this process is a few hundreds of femtoseconds. Then in the hole-doped correlated metallic titanate, we show how pure spin-currents can be achieved to yield spin-polarizations exceeding those observed in classic semiconductors. Last, we demonstrate the generality of the approach by applying it to the non-orbitally degenerate AFM CaMnO 3 . These results advance our understanding of electron-lattice interactions in structures out-of-equilibrium and establish a rational framework for designing dynamic phases that may be exploited in ultrafast optoelectronic and optospintronic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2026

2D nanoconfinement distorts the solvation structure of hydroxide but not of hydronium

Understanding ion-specific behavior in nanoconfined water is essential for controlling charge transport and selectivity in two-dimensional membranes. Motivated by recent experiments revealing anomalous dielectric and transport behavior of water confined between hBN sheets, we use machine-learning-accelerated first-principles molecular dynamics to investigate the interfacial propensities of hydronium and hydroxide ions under similar confinement. We find that hydronium remains interfacial across all confinement regimes, whereas hydroxide shifts toward the interior as the environment becomes more bulk-like. This contrasting behavior reflects the combined influence of hydrogen bonding, interfacial water layering, and the polarization of hBN, which collectively stabilize hydronium at the surface while making hydroxide slightly more favorable within the structured interior. These findings expose an asymmetry in ion-surface coupling and establish a microscopic origin for hydronium’s enhanced interfacial affinity. The results provide mechanistic insight into ion partitioning in two-dimensional channels and highlight the collective structuring of confined water as a key determinant of interfacial ion thermodynamics.

organic↗
DOE OSTI2024

Event Detection and Classification Using Machine Learning Applied to PMU Data for the Western US Power System

Smart grid technology enhances our comprehension and reliability of the power grid, leveraging Phasor Measurement Unit (PMU) data—time-synchronized, high-frequency measurements gathered across the US power grid. This paper employs machine learning techniques to effectively analyze the vast PMU data in Wide Area Monitoring Systems (WAMS) for power grid event detection and classification. Analyzing several months of real-world PMU data, the paper focuses on machine learning for fast, precise event detection and classification, corroborated by utility event logs. Practical challenges like feature extraction, dimensionality reduction, and model selection are addressed. A novel feature yielding improved results is discovered, and a supplementary algorithm for detecting small power grid faults is developed. The final algorithm is validated using a month-long real PMU data set, demonstrating its capability in accurately identifying power grid events in near real-time.

machine learning, event detection, PMU↗
DOE OSTI2014

WE-E-17A-02: Predictive Modeling of Outcome Following SABR for NSCLC Based On Radiomics of FDG-PET Images

Purpose: This study aims to develop predictive models of patient outcome by extracting advanced imaging features (i.e., Radiomics) from FDG-PET images. Methods: We acquired pre-treatment PET scans for 51 stage I NSCLC patients treated with SABR. We calculated 139 quantitative features from each patient PET image, including 5 morphological features, 8 statistical features, 27 texture features, and 100 features from the intensity-volume histogram. Based on the imaging features, we aim to distinguish between 2 risk groups of patients: those with regional failure or distant metastasis versus those without. We investigated 3 pattern classification algorithms: linear discriminant analysis (LDA), naive Bayes (NB), and logistic regression (LR). To avoid the curse of dimensionality, we performed feature selection by first removing redundant features and then applying sequential forward selection using the wrapper approach. To evaluate the predictive performance, we performed 10-fold cross validation with 1000 random splits of the data and calculated the area under the ROC curve (AUC). Results: Feature selection identified 2 texture features (homogeneity and/or wavelet decompositions) for NB and LR, while for LDA SUVmax and one texture feature (correlation) were identified. All 3 classifiers achieved statistically significant improvements over conventional PET imaging metrics such as tumor volume (AUC = 0.668) and SUVmax (AUC = 0.737). Overall, NB achieved the best predictive performance (AUC = 0.806). This also compares favorably with MTV using the best threshold at an SUV of 11.6 (AUC = 0.746). At a sensitivity of 80%, NB achieved 69% specificity, while SUVmax and tumor volume only had 36% and 47% specificity. Conclusion: Through a systematic analysis of advanced PET imaging features, we are able to build models with improved predictive value over conventional imaging metrics. If validated in a large independent cohort, the proposed techniques could potentially aid in identifying patients who might benefit from adjuvant therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Poster — Thur Eve — 62: A Retrospective Assessment of the Prevalence and Dosimetric Effect of Lateral Electron Disequilibrium in a Population of Lung Cancer Patients Treated by Stereotactic Body Radiation Therapy

Stereotactic Body Radiation Therapy (SBRT) is a treatment option for early stage non-small cell lung cancer (NSCLC). SBRT uses tightly conformed megavoltage (MV) x-ray beams to ablate the tumour. However, small MV x-ray fields may produce lateral electron disequilibrium (LED) within lung tissue, which can reduce the dose to tumour. The goal of this work is to estimate the prevalence of LED in NSCLC patients treated with SBRT, and determine dose effects for patients prone or averse to LED. Thirty NSCLC patients were randomly selected for analysis. 4-dimensional CT lung images were segmented into the right and left upper and lower lobes (RUL, RLL, LUL, LLL), and the right middle lobe. Dose calculations were performed using volume-modulated arc therapy in the Pinnacle{sup 3} TPS. Most tumours were located in the upper lobes (RUL 53%, LUL 27%) where density was significantly lower (RUL −808±46 HU vs. RLL −743±71 HU; LUL −808 ±56 HU vs. LLL −746±70 HU; p<0.001). In general, the prevalence of LED increased with higher beam energy. Using 6MV photons, patients with a RUL tumour experienced moderate (81 %), and mild (19%) levels of LED. At 18MV, LED became more prominent with severe (50%) and moderate (50%) LED exhibited. Dosimetrically, for patients prone to LED, poorer target coverage (i.e. increased R100 by 20%) and improved lung sparing (i.e. reduced V20 by −46%) was observed. The common location of lung cancers in the upper lobes, coupled with lower lung density, results in the potential occurrence of LED, which may underdose the tumour.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Selective UV radiation detection on the basis of low-dimensional ZnCdS/ZnMgS/GaP and ZnCdS/ZnS/GaP heterostructures

The detecting properties of periodic heterostructures with ZnCdS quantum wells separated by ZnMgS or ZnS barrier layers are studied. Heterostructures are grown on semi-insulating GaP substrates by metal organic vapor-phase epitaxy (MOVPE). On their basis, metal–semiconductor–metal (MSM) diodes with interdigital Schottky contacts 3 μm, distances between them of 3 μm, and a total detector area of 100 × 100 μm are fabricated. The detectors have low dark currents (10{sup –12} A); at low bias voltages, they provide a narrow- band response (full-width at half-maximum of FWHM = 18 nm at a wavelength of 350 nm) which is controlled by the ZnCdS quantum-well composition. As bias is increased to 70 V, the maximum detector sensitivity shifts by a wavelength of 450 nm, which is caused by penetration of the external-bias electric field into the semi-insulating GaP substrate. In this case, the narrow-band response of the detector at a wavelength of 350 nm is retained, i.e., the two-color detection of light is provided.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Characterization of a Low-Temperature Plasma (LTP) Ambient Ionization Source Using Temporally Resolved Monochromatic Imaging Spectrometry

The low-temperature plasma (LTP) probe is a common plasma-based source used for ambient desorption–ionization mass spectrometry (MS). While the LTP probe has been characterized in detail with MS, relatively few studies have used optical spectroscopy. In this paper, two-dimensional (2D) imaging at selected wavelengths is used to visualize important species in the LTP plasma jet. First, 2D steady-state images of the LTP plume for N 2 + (391.2 nm), He I (706.5 nm), and N 2 (337.1 nm) emissions were recorded under selected plasma conditions. Second, time-resolved 2D emission maps of radiative species in the LTP plasma jet were recorded through the use of a 200 ns detection gate and varying gate delays with respect to the LTP trigger pulse. Emission from He I, N 2 + , and N 2 in the plasma jet region was found to show a transient behavior (often referred to as plasma bullets) lasting only a few microseconds. The N 2 + and He I maps were highly correlated in spatial and temporal structure. Further, emission from N 2 showed two maxima in time, one before and one after the maximum emission for N 2 + and He I, due to an initial electronic excitation wave and ion–electron recombination, respectively. Third, the interaction of the LTP probe with a sample substrate and an electrically grounded metallic needle was studied. Emission from a fluorophore on the sample substrate showed an initial photon-induced excitation from plasma-generated photons followed by electronic excitation by other plasma species. The presence of a grounded needle near the plasma jet significantly extended the plasma jet lifetime and also generated a long-lived corona discharge on the needle. The effect of LTP operating parameters on emission spectra was correlated with mass-spectral results including reagent-ion signals. Lastly, five movies provide a side-by-side comparison of the temporal behavior of emitting species and insights into the interactions of the emission clouds with a sample surface as well as an external needle. Temporally and spatially resolved imaging provided insights into important processes in the LTP plasma jet, which will help improve analyte ion sampling in LTP–MS.

Chan, George C. -Y.↗
DOE OSTI2026

Heterogeneous Multi-Domain Dataset Synthesis to Facilitate Privacy and Risk Assessments in Smart City IoT

The emergence of the Smart Cities paradigm and the rapid expansion and integration of Internet of Things (IoT) technologies within this context have created unprecedented opportunities for high-resolution behavioral analytics, urban optimization, and context-aware services. However, this same proliferation intensifies privacy risks, particularly those arising from cross-modal data linkage across heterogeneous sensing platforms. To address these challenges, this paper introduces a comprehensive, statistically grounded framework for generating synthetic, multimodal IoT datasets tailored to Smart City research. The framework produces behaviorally plausible synthetic data suitable for preliminary privacy risk assessment and as a benchmark for future re-identification studies, as well as for evaluating algorithms in mobility modeling, urban informatics, and privacy-enhancing technologies. As part of our approach, we formalize probabilistic methods for synthesizing three heterogeneous and operationally relevant data streams—cellular mobility traces, payment terminal transaction logs, and Smart Retail nutrition records—capturing the behaviors of a large number of synthetically generated urban residents over a 12-week period. The framework integrates spatially explicit merchant selection using K-Dimensional (KD)-tree nearest-neighbor algorithms, temporally correlated anchor-based mobility simulation reflective of daily urban rhythms, and dietary-constraint filtering to preserve ecological validity in consumption patterns. In total, the system generates approximately 116 million mobility pings, 5.4 million transactions, and 1.9 million itemized purchases, yielding a reproducible benchmark for evaluating multimodal analytics, privacy-preserving computation, and secure IoT data-sharing protocols. To show the validity of this dataset, the underlying distributions of these residents were successfully validated against reported distributions in published research. We present preliminary uniqueness and cross-modal linkage indicators; comprehensive re-identification benchmarking against specific attack algorithms is planned as future work. This framework can be easily adapted to various scenarios of interest in Smart Cities and other IoT applications. By aligning methodological rigor with the operational needs of Smart City ecosystems, this work fills critical gaps in synthetic data generation for privacy-sensitive domains, including intelligent transportation systems, urban health informatics, and next-generation digital commerce infrastructures.

IoT↗