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DOE OSTI2025

Selective deuteration of an RNA:RNA complex for structural analysis using small-angle scattering

The structures of RNA:RNA complexes regulate many biological processes. Despite their importance, protein-free RNA:RNA complexes represent a tiny fraction of experimentally determined structures. Here, we describe a joint small-angle X-ray and neutron scattering (SAXS/SANS) approach to structurally interrogate conformational changes in a model RNA:RNA complex. Using SAXS, we measured the solution structures of the individual RNAs and of the overall RNA:RNA complex. With SANS, we demonstrate, as a proof of principle, that isotope labeling and contrast matching (CM) can be combined to probe the bound state structure of an RNA within a selectively deuterated RNA:RNA complex. Furthermore, we show that experimental scattering data can validate and improve predicted AlphaFold 3 RNA:RNA complex structures to reflect its solution structure. In conclusion, our work demonstrates that in silico modeling, SAXS, and CM-SANS can be used in concert to directly analyze conformational changes within RNAs when in complex, enhancing our understanding of RNA structure in functional assemblies.

HIV-1 dimerization initiation site↗

DOE OSTI2025

Improving adhesive bonding of short carbon fiber thermoplastic composites to aluminum alloys with a hybrid laser-plasma surface modification strategy

This study investigates hybrid laser–plasma surface modification strategies for metal–CFRTP (carbon-fiber-reinforced thermoplastic polymer) dissimilar joints to improve their bonding performance, in contrast to existing literature that mostly focuses on either plasma or laser treatment alone. By conducting double cantilever beam (DCB) tests on adhesively-bonded AA5052 and CFRPA66 (carbon-fiber-reinforced polyamide 66) joints, as an example of metal–CFRTP joints, it was found that laser engraving on the metal surface combined with plasma treatment on the CFRTP surface significantly improved the specific fracture energy of the joint by 187% and 31% compared to as-received and plasma-treated-only joints, respectively. However, the hybrid treatment of laser engraving and plasma on the investigated CFRTP surface did not improve the bonding performance of the joints. The underlying mechanisms related to hybrid laser-plasma surface modification strategies were further investigated by examining the surface and cross-sectional morphologies after DCB testing using microscopy. Computational modeling was performed to elucidate the interaction between grooves on the metal substrate and the CFRTP–adhesive interfacial bonding in metal–CFRTP joints. This study provides new insights into developing surface modification methods for achieving strong metal–CFRTP adhesive joints, aimed at lightweighting structural components in automotive, aerospace, and other applications.

Adhesive bonding↗

DOE OSTI2026

Demonstration of high-rate manufacturing of π-joint using additive manufacturing

Bonded composite π-joints are critical to support wing geometries in aerospace/aircraft structures. Its lightweight and robust load-bearing capabilities/design guarantee high structural integrity and reliability. Current manufacturing techniques of π-joints are complex and laborious, and do not always offer high-quality joining. This study presents a high-rate manufacturing approach to fabricate π-joints using an integrated Additive Manufacturing and Compression Molding (AMCM) process. The joints were manufactured using unidirectional aerospace-grade LMPAEK/CF at 60% fiber loading for the stiffeners/skin and LM-PAEK/GF as the adhesive and characterized to evaluate their microstructure and strength. While the results indicate void formation at the joint caused by inadequate pressure, the peak tensile load of 600N recorded is akin to injection-autoclave molded π-joints, which validates the potential of this high-rate integrated approach to eliminate time-consuming and labour-intensive processes of making π-joints to reduce cost and produce high-quality joints.

Marathe, Umesh [ORNL]↗

DOE OSTI2024

Resonant inelastic x-ray scattering in the topological semimetal FeSi

The energy spectrum of topological semimetals contains protected degeneracies in reciprocal space that correspond to Weyl, Dirac, or multifold fermionic states. To exploit the unconventional properties of these states, one has to access the electronic structure of the three-dimensional bulk. In this paper, we present a joint theory-experiment study of the electronic structure of a candidate topological semimetal with resonant inelastic x-ray scattering (RIXS). We resolve the bulk electronic states of FeSi using momentum-dependent RIXS at the Fe L 3 edge. We observe a broad excitation continuum devoid of sharp features, consistent with particle-hole scattering in an underlying electronic band structure. Using density functional theory (DFT), we calculate the electronic structure of FeSi and derive a band theory formulation of RIXS in the fast collision approximation to model the scattering process with zero adjustable parameters. While band theory predicts an excitation continuum with broad spectral features similar to the observed ones, discrepancies between theory and experiment suggest the presence of low-energy processes that DFT alone does not account for. Further, this study of RIXS in a topological semimetal shows that RIXS is a useful tool for revealing unanticipated behavior of bulk electronic states in this class of materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

The Collaborative Seismic Earth Model: Generation 2

Geological interpretations, earthquake source inversions and ground motion modeling, among other applications, require models that jointly resolve crustal and mantle structure. With the second generation of the Collaborative Seismic Earth Model (CSEM2), we present a global multi-resolution tomographic Earth model that serves this purpose. The model evolves through successive regional- and global-scale refinements. While the first generation aggregated regional models, with this study, we ensure consistency between all individual submodels, resulting in a model that accurately explains wave propagation across scales. Recent regional tomographic models were incorporated, comprising continental-scale inversions for Asia and Africa, as well as regional inversions for the Western US, Central Andes, Iran, and Southeast Asia. Across all regional refinements, over 793,000 source-receiver pairs contributed. Moreover, the long-wavelength Earth model (LOWE) introduces large-scale structures outside of pre-existing local refinements. A full-waveform inversion for global anisotropic P-and S-wave speed structure over a total of 194 iterations with a minimum period of 50 s on a large data set of 1 hr of waveform data from 2,423 earthquakes and over 6 million source-receiver pairs ensures that regional updates in the crust and uppermost mantle translate into updates of deeper, global-scale structure. To test the performance of CSEM2, we evaluate waveform fits between observed and synthetic seismograms at 50 s for an independent data set on the global scale, and on the regional scale for lower periods. We accurately simulate waveforms within and across regional refinements, maintaining the original resolution of the submodels embedded in the global framework.

58 GEOSCIENCES↗

DOE OSTI2025

Low-Cost Sulfur Thermal Storage for Solar Industrial Process Heat Applications

Industrial process heat (IPH) is one of the largest energy demands in U.S., representing about 10% of all domestic energy consumption. Fuel costs to generate this industrial process heat are generally a top three cost for industry, a major component in American manufacturing competitiveness. Roughly 60% of US IPH demand (about 6,500 TBtu annually) falls in the medium-temperature range of 100–250 °C. While concentrated solar thermal (CST) technologies can provide a cost-effective source of heat in this temperature range, solar intermittency limits their adoption in industries that operate 24/7. Element 16 Technologies, Inc. developed a low-cost sulfur thermal energy storage (TES) technology to bridge this gap by capturing excess solar heat during the day and dispatching it reliably during non-solar hours. The core innovation is the use of sulfur, an abundant, industrial waste byproduct that costs ten times less than molten salt used in commercial TES systems. The overall goal of the project was to advance the design and development of molten sulfur TES to a manufacturing-relevant prototype stage for solar industrial process heat applications, while establishing and validating a realistic pathway to commercial success. Key tasks included corrosion and mechanical durability testing to identify cost-effective materials, design investigations using physics-based simulation tools, techno-economic evaluations of system lifetime costs, and pilot-scale testing for performance verification. Corrosion testing of steel alloys under cyclic molten sulfur conditions showed that austenitic stainless steels in the 300 series performed particularly well, with no structural degradation of welds or joints. Thermal cyclic testing of pilot sulfur TES units up to 1.5 MWh quantified charge/discharge rates, heat losses, round-trip efficiency and validated the system's capability to operate effectively under intermittent charging conditions. A techno-economic model, informed by sulfur TES performance model validated using pilot test data, showed that hybrid solar+sulfur TES+NG boiler systems are economically competitive with incumbent natural gas boilers for multiple locations in the southwest US. In summary, this project established molten sulfur TES as a technically viable pathway to improve economic competitiveness of American manufacturing by lowering the cost of solar industrial process heat.

14 SOLAR ENERGY↗

DOE OSTI2025

A joint analysis of 3D clustering and galaxy × CMB-lensing cross-correlations with DESI DR1 galaxies

The spectroscopic data from DESI Data Release 1 (DR1) galaxies enables the analysis of 3D clustering by fitting galaxy power spectra and reconstructed correlation functions in redshift space. Given low measurements of the amplitude of structure from cosmic shear at z ∼ 1, redshift space distortions (RSD) + Baryon Acoustic Oscillation (BAO) signals from DESI galaxies combined with weak lensing can break degeneracies and provide a tight alternative constraint on the z ∼ 1 amplitude of structure. In this paper we perform joint analyses that combine full-shape + post-reconstruction information from the DESI DR1 BGS and LRG samples along with angular cross-correlations with Planck PR4 and ACT DR6 CMB lensing maps. We show that adding galaxy-lensing cross-correlations tightens clustering amplitude constraints, improving σ 8 uncertainties by 30% over RSD+BAO alone. We also include angular galaxy-galaxy and galaxy-lensing spectra using photometric samples from the DESI Legacy Survey to further improve constraints. Our headline results are σ 8 = 0.803 ± 0.017, Ω m = 0.3037 ± 0.0069, and S 8 = 0.808 ± 0.017. Given DESI's preference for higher σ 8 compared to lower values from BOSS, we perform a catalog-level comparison of LRG samples from both surveys. We test sensitivity to dark energy assumptions by relaxing our ΛCDM prior and allowing for evolving dark energy via the w 0 - w a parameterization. We find our S 8 constraints to be relatively unchanged despite a 3.5σ tension with the cosmological constant model when combining with the Union3 supernova likelihood. Finally we test general relativity (GR) by allowing the gravitational slip parameter (γ) to vary, and find γ = 1.17 ± 0.11 in mild (∼ 1.5σ) tension with the GR value of 1.0.

cosmological parameters from LSS↗

DOE OSTI2025

Resolving the Solvation Structure and Transport Properties of Aqueous Zinc Electrolytes from Salt-in-Water to Water-in-Salt Using Neural Network Potential

Zn Cl 2 solutions are promising electrolytes for aqueous zinc-ion batteries. Here, we report a joint computational and experimental study of the structural and dynamic properties of aqueous Zn Cl 2 electrolytes with concentrations ranging from salt-in-water to water-in-salt (WIS). By developing a neural network potential (NNP) model, we perform molecular dynamics (MD) simulations with accuracy but at much larger lengths and longer timescales. The NNP predicted structures are validated by the structure factors measured by X-ray total scattering experiments. The MD trajectories provide a comprehensive and quantitative picture of the Zn 2 + solvation shell structures. Additionally, we find that the O − H covalent bonds in water are strengthened with increasing salt concentration, thus expanding the electrochemical stability window of aqueous electrolytes. In terms of dynamic properties, the calculated and experimentally measured conductivities are in good agreement. Through the analysis of the calculated cation transference number, we propose a three-stage charge carrier transport mechanism with increasing concentration: independent ion transport, strongly correlated ion transport, and small positive charge carrier diffusion through negatively charged polymeric clusters. Our study provides fundamental atomic scale insights into the structure and transport properties of the Zn Cl 2 electrolyte that can aid the optimization and development of WIS electrolytes. Published by the American Physical Society 2025

25 ENERGY STORAGE↗

DOE OSTI2026

Corrosion Resistance of Lignin-Based Thermoplastic Adhesive-Bonded Aluminum Joints

Adhesive-bonded joints are essential for lightweight, multimaterial automotive structures. We developed a lignin-based thermoplastic adhesive with adhesion strength comparable to conventional epoxy adhesives (20–23 MPa), while offering exceptional durability, recyclability, and corrosion resistance. Unlike commercial epoxy adhesives requiring refrigerated storage, our adhesive retains its bonding potential after a year of ambient conditioning. Bonded joints can be repeatedly disassembled and rejoined with less than 2% strength loss. After 500 h of salt fog exposure, the adhesive-bonded aluminum joints exhibited a 24% strength reduction, compared to 61% reduction in strength of joints based on a commercial epoxy adhesive.

Yu, Zeyang [ORNL] (ORCID:0000000209002374)↗

DOE OSTI2025

Flower‐Type Organized Trade‐Wind Cumulus: A Multi‐Day Lagrangian Large Eddy Simulation Intercomparison Study

Shallow cumulus cloud fields in subtropical marine trade wind environments, particularly over the tropical Atlantic Ocean, show distinct organizational patterns. Among these, Flower‐type clouds are characterized by expansive stratiform cloud patches surrounded by regions of scattered convection. The objectives of this study were (a) to construct a case study of a time period during the EUREC 4 A/ATOMIC field campaign when Flower‐type organization was observed, (b) to evaluate the fidelity of a multi‐model ensemble of large eddy simulations of that case, and (c) to analyze the interaction between cloud and precipitation processes and mesoscale organization in the simulations. The simulations follow a quasi‐Lagrangian trajectory, allowing mesoscale features to develop over time in a domain that follows the boundary‐layer airmass. The results show a broad agreement in simulated thermodynamic properties across different LES codes, with Flower‐type cloud patches appearing within hours of each other. The consensus among models is consistent with observations made during the EUREC 4 A/ATOMIC field campaign on the specific day of interest. The cloud structure reveals three distinct peaks in the joint probability densities of cloud base and cloud top height, with the dominant peak at any given time influenced by the stage of cloud organization. The simulated cloud system evolution reveals consistent occurrence of maxima in liquid water path and rain rate before Flower reaches its maximum length scale. Targeted sensitivity tests reveal a weak relationship between Cloud Droplet Number concentration and the extent/degree/type of organization.

EUREC4A↗

DOE OSTI2025

Systematic input scheme for many-boson Hamiltonians with applications to the two-dimensional 𝜙 4 theory

We develop a novel, systematic input scheme for many-boson Hamiltonians in order to solve field theory problems within the light-front Hamiltonian formalism via quantum computing. We present our discussion of this input scheme based on the light-front Hamiltonian of the two-dimensional ϕ 4 theory. In our input scheme, we employ a set of quantum registers, where each register encodes the occupation of a distinct boson mode as binaries. We squeeze the boson operators of each mode and present the Hamiltonian in terms of unique combinations of the squeezed-boson operators. We design the circuit modules for these unique combinations. Based on these circuit modules, we block encode the many-boson Hamiltonian utilizing the idea of quantum walk. For demonstration purposes, we present the spectral calculations of the Hamiltonian utilizing the hybrid quantum-classical symmetry-adapted quantum Krylov subspace diagonalization algorithm based on our input scheme, where the quantum computations are performed with the IBM Qiskit quantum simulator. The results of the hybrid calculations agree with exact results. Here, we can incorporate the input scheme in this work with the input scheme for many-fermion Hamiltonians; they jointly offer new pathways to solving the structure and dynamics of more general field theory problems on future fault-tolerant quantum computers.

Ab initio calculations↗

DOE OSTI2025

Fitness For Service Assessment of a Corroded Heat Exchanger

Within the Fermi National Accelerator complex, there exist various water systems that support accelerator operations. One of these systems is extremely vital to the operation of the machine; that is the cooling system. The cooling system consists of nine relatively large heat exchangers that take untreated pond water and use it to cool the process fluid that further cools machine components. Over the 30 years these heat exchangers have been in operation, they have undergone significant material loss on the channels. This material loss, due to various forms of corrosion such as galvanic and microbiologically influenced corrosion (MIC) and possibly others, has deteriorated more than 80% of the nominal wall thickness of some of the exchangers and placed them in a questionable state. ASME FFS-1 (API 579) has been applied to address the condition of the heat exchangers due to their noncompliance with the governing code, BPVC Sec. VIII Div. 1. The assessments encompassed ASME FFS-1 parts 4: General Metal Loss and 9: Crack Like Flaw using level 1, 2, and 3 analysis techniques based on inspection data obtained by API 510 inspections. Level 1 and 2 assessments were deemed unfit for the corroded regions due to their location relative to a major structural discontinuity (channel to tube-sheet joint), so a level 3 analysis was conducted according to ASME Sec. VIII Div. 2 (design by analysis) rules for pressure vessels. Supplemental information included pond water tests to determine an accurate future corrosion allowance due to lacking inspection history. A leak before break (LBB) route was chosen to evaluate the possibility of leaking prior to the onset of failure. The analysis of one heat exchanger shows that the possibility the channel will develop a pinhole leak over 2.5 more years of operation should not be overlooked, but burst was unlikely from operation. The use of fracture mechanics show, that if a through-wall crack were to develop, it would not propagate further than the channel geometry and cause a leak not greater than 35 GPM. Using ASME Section XI Code Case N-705-1, allowing us to operate with a leak until the next outage given certain operating conditions and developing a leak mitigation procedure, this heat exchanger is deemed fit-for-service.

Humenik, Alex [Fermilab]↗

DOE OSTI2025

SigTime: Learning and Visually Explaining Time Series Signatures

Understanding and distinguishing temporal patterns in time series data is essential for scientific discovery and decision-making. For example, in biomedical research, uncovering meaningful patterns in physiological signals can improve diagnosis, risk assessment, and patient outcomes. However, existing methods for time series pattern discovery face major challenges, including high computational complexity, limited interpretability, and difficulty in capturing meaningful temporal structures. Here, to address these gaps, we introduce a novel learning framework that jointly trains two Transformer models using complementary time series representations: shapelet-based representations to capture localized temporal structures and traditional feature engineering to encode statistical properties. The learned shapelets serve as interpretable signatures that differentiate time series across classification labels. Additionally, we develop a visual analytics system—SigTime—with coordinated views to facilitate exploration of time series signatures from multiple perspectives, aiding in useful insights generation. We quantitatively evaluate our learning framework on eight publicly available datasets and one proprietary clinical dataset. Additionally, we demonstrate the effectiveness of our system through two usage scenarios along with the domain experts: one involving public ECG data and the other focused on preterm labor analysis.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Manufacturing Full-Scale High Gradient Copper Accelerators: Electron Beam Welding and Allied Processes

This DOE ARDAP-funded study examines the technical and business feasibility of manufacturing high-gradient normal conducting RF (NCRF) copper accelerating structures using electron beam welding (EBW) instead of conventional high-temperature brazing. The core motivation is material performance: brazing softens copper significantly, while hard copper alloys have demonstrated ~75% higher operational gradients in SLAC tests, making cold-joining techniques highly attractive. EBW, applied to split-cell (half or quadrant) structure designs, preserves copper hardness away from the weld joint and simplifies machining — but industrial process optimization remains immature and a substantial learning curve is expected. The business case was modeled for two scenarios: a greenfield EBW linac company (> $10M upfront costs, viable above ~30 units/year) and an EBW division added to an existing accelerator firm to reduce risk and upfront costs, at the expense of being less optimal structure for the higher volume production. The study concludes that without a significant increase in demand, private investment alone cannot sustain this capability, and recommends federal support through R&D grants, procurement incentives, and CAPEX cost-sharing to incubate domestic EBW-NCRF manufacturing — with the existing-company model.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

Neural chaos: A spectral stochastic neural operator

Building surrogate models for operators with uncertainty quantification capabilities is essential for many engineering applications where randomness–such as variability in material properties, boundary conditions, and initial conditions–is unavoidable. Polynomial Chaos Expansion (PCE) is widely recognized as a go-to method for constructing stochastic surrogates in both intrusive and non-intrusive ways, and it has recently been used in the context of operator learning. However, its application becomes challenging for complex or high-dimensional processes, as achieving accuracy requires higher-order polynomials, which can increase computational demand and/or the risk of overfitting. Furthermore, PCE requires specialized treatments to manage random variables that are not independent, and these treatments may be problem-dependent or may fail with increasing complexity. Here, in this work, we adopt the same formalism as the spectral expansion used in PCE; however, we replace the classical polynomial basis functions with neural network (NN) basis functions to leverage their expressivity. To achieve this, we propose an algorithm that identifies NN-parameterized basis functions in a purely data-driven manner, without any prior assumptions about the joint distribution of the random variables involved, whether independent or dependent, or about their marginal distributions. The proposed algorithm identifies each NN-parameterized basis function sequentially, ensuring they are orthogonal with respect to the data distribution. The basis functions are constructed directly on the joint stochastic variables without requiring a tensor product structure or assuming independence of the random variables. This approach may offer greater flexibility for complex stochastic models, while simplifying implementation compared to the tensor product structures typically used in PCE to handle random vectors. This is particularly advantageous given the current state of open-source packages, where building and training neural networks can be done with just a few lines of code and extensive community support. We demonstrate the effectiveness of the proposed scheme through several numerical examples of varying complexity and provide comparisons with classical PCE.

Polynomial chaos expansion↗

DOE OSTI2026

Mapping resonant inelastic x-ray scattering onto electronic structure of iridium compounds

Resonant inelastic X-ray scattering (RIXS) is an indispensable tool that can selectively probe the electronic structure of active sites in energy conversion systems, for example, iridium oxides. However, decoding the RIXS spectra remains challenging due to its inherently complex many-body interactions. Here, we analyze Ir L 3 edge RIXS spectra of Ir, IrCl 3 , and IrO 2 , employing the joint density of states (JDOS) calculated directly from electronic band-structure calculations. The overall energy-loss features in the RIXS spectra are well reproduced by the JDOS, reaffirming the close correspondence between electron–hole excitations and RIXS spectra observed in prior studies. Intriguingly, the RIXS spectra above ∼4 eV in metallic Ir and IrO 2 follow a power-law behavior, 𝐼 RIXS ~Δ −𝑝 , where Δ is the energy loss and p is the associated power-law exponent. This is consistent with edge-singularity behavior commonly found in resonant X-ray scattering from metallic samples. Furthermore, orbital-projected JDOS enables a decomposition of the IrO 2 spectrum into specific dd transitions, providing a clear interpretation of orbital excitations and an efficient strategy for decoding RIXS spectra in iridium-based energy conversion systems.

5d↗

DOE OSTI2025

Investigation of Site Amplifications Using Ambient-Noise-Derived Shallow Velocity Structures Under a Dense Array in Oklahoma

The shear-wave velocity (V S ) structure plays an important role in characterizing site amplification. The Large-n Seismic Survey in Oklahoma (LASSO; 1820 stations) revealed large vertical ground-motion variability in a 25 km × 32 km area in northern Oklahoma. The LASSO array has a relatively simple and flat topography, typical in a sedimentary basin environment in the central United States. In this study, we use the dense array to investigate the velocity structure under the LASSO array and how vertical ground motions relate to the shallow-to-deep structures. We extract the fundamental-mode Rayleigh wave by cross-correlating one month of ambient noise (0.7–5 Hz). We use double-beamforming to measure the group and phase velocities and anisotropy. By jointly inverting the group and phase velocities, we obtain the V S structure. Here, we observe correlations between V S at depths of 0.1–1.5 km and vertical ground motions using sites on the stiffer Permian formations. The shallow Quaternary alluvium and terrace deposits can amplify vertical ground motions by a factor of 2–4.5 between 2 and 25 Hz and attenuate signals above 25 Hz. We use 1D V S profiles to simulate the SV-wave transfer functions. An average V S of 250 m/s in the upper 20–40 m may cause the observed amplification between 2 and 40 Hz. V S estimated by topographic slopes cannot predict the relative amplification. Our results highlight the large variability of site-dependent ground motion in a small local region and the importance of characterizing shallow structures to estimate seismic hazards. Small thickness variations of the shallow formation can significantly change the resonance amplitude and frequency, which likely reduces the coherency of the Rayleigh waves extracted from ambient noise.

Chang, Hilary [Massachusetts Inst. of Technology (↗

DOE OSTI2024

Testing and modeling of CLT-to-CLT joints made using hardwood dowels and screws with varying spacing

With the increasing popularity of mass timber, utilizing large-diameter wood screws and hardwood dowels can offer an easy and cost-efficient way to join structural elements. However, the existing research on hardwood dowels is limited to single fastener joints under monotonic loading. No research is available on the group effects of joints with multiple hardwood dowels. Here, this paper presents the results of 96 monotonic and cyclic single-shear plane CLT-to-CLT joint tests with hardwood dowels (Red Oak and Yellow Birch, 25.4 mm diameter) and self-tapping wood screws (8 mm diameter) in Grand-Fir CLT, where screws were inserted both perpendicular and at a 45-degree angle to the grain for comparison to hardwood dowels. The study evaluated the mechanical properties of the joints by changing fastener spacing. Mechanical properties such as yielding and peak strength, displacement, elastic and yielding stiffness, and ductility were evaluated. The results showed equal strength and stiffness properties for hardwood dowels comparable with large-diameter screws. Additionally, the hardwood dowel joints demonstrated moderate ductility properties. The strength and stiffness of the tested joints were compared with analytical equations found in the literature by considering the group action factor of the fasteners. Lastly, a nonlinear force-displacement model was presented and compared to the experimental results and analytical calculations, which gives the possibility to predict and optimize the mechanical behavior of hardwood dowel and screw joints with varying numbers and spacing between fasteners.

36 MATERIALS SCIENCE↗