Title: Hyper Drive Dynamics and Warp Drive Diagnostics: A Data Driven Study of Hyperspherical Bessel Shells, Tensor Audits, and $S^8$ ADM Metric Optimization Abstract / Description: This research paper presents a computational and constructive framework for general relativistic warp drive metric engineering. Beginning with an Alcubierre-style shift metric, the traditional warp shape function is generalized into a hyperspherical Bessel-breathing shell program. The model is systematically audited across four increasingly concrete computational layers: a reduced axisymmetric EinsteinPy diagnostic, a full moving-bubble 3+1 Cartesian EinsteinPy diagnostic, an $S^1$ through $S^8$ constrained shell optimizer, and a coordinated $S^8$-dominant ADM (Arnowitt-Deser-Misner) metric-component optimizer. Rather than bypassing energy condition tests, this study treats hyperspherical and Bessel modes as structured mechanisms to redistribute, reduce, and smooth peak gradient penalties in the effective stress-energy tensor. Key computational findings demonstrate that a higher-dimensional $S^8$ Bessel wall basis yields optimal energy proxy distributions, while coordinated shaping of the lapse ($\alpha$), shift ($\beta$), and spatial metric ($\gamma$) provides substantial improvements over baseline step-like or hyperbolic tangent profiles. Additionally, the study maps the metric's auxiliary diagnostic structures, exploring magneto-acoustic statistics, dimensional accessibility resonances, and helicity/winding-lock defects. This deposit includes the full reproducible diagnostic dataset backing the analysis, spanning metric slice profiles, energy condition scans, curvature scalar calculations, and optimizer weight matrices.